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[72jueji.com] Udacity - Data Analyst Nanodegree v1.0.0
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[72jueji.com] Udacity - Data Analyst Nanodegree v1.0.0
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文件列表
Part 12-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier-qRv1wrtgsmM.mp4
118.9 MB
Part 12-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-i3RTW83wI1Q.mp4
112.4 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/07. Coding-zhQYREUI8Z0.mp4
110.1 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/08. Coding 2-qEteyPNRSwU.mp4
109.7 MB
Part 11-Module 01-Lesson 06_Datasets and Questions/01. Introduction-TdopVWltgqM.mp4
92.2 MB
Part 06-Module 01-Lesson 03_Analyzing Data/19. Geospatial Indexes-iGnSNfzaLf4.mp4
71.2 MB
Part 06-Module 01-Lesson 03_Analyzing Data/11. Unwind Operator-6wBjB3Ca5H4.mp4
61.3 MB
Part 12-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability-Zyq0FQ0XO3o.mp4
59.4 MB
Part 14-Module 01-Lesson 05_Analyzing Results/09. Single Metric Example-LCZG4wlEFXE.mp4
56.3 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/29. Lessons Learned-_dnp6ItYOdA.mp4
55.4 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/49. The Future of Data Visualizations--CWbVBYBYWU.mp4
55.2 MB
Part 12-Module 01-Lesson 05_Interview Practice/04. Query a SQL database-UVSFLWdAKl4.mp4
53.6 MB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/01. Data Visualization Resources-OYl-saB2vWE.mp4
52.9 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/15. JSON Playground-la_rboWWjQI.mp4
52.4 MB
Part 12-Module 01-Lesson 03_Interview Fails/04. Interviewing Fails Lyla Fujiwara-CgK2HxdJzc8.mp4
52.2 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/16. Sean's NFL Fan Sentiment Study-ahaxt6UKxQw.mp4
52.0 MB
Part 14-Module 01-Lesson 05_Analyzing Results/16. Analyzing Multiple Metrics-mbHnQ_EdrZ8.mp4
52.0 MB
Part 04-Module 03-Lesson 01_Investigate a Dataset/05. Investigate A Dataset Project Walkthrough Final-OtDZCYxbHB4.mp4
51.8 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/23. Learning Effects-nFpIDWPUDm8.mp4
51.4 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/09. Using CSV Module--S4vc6tvxoI.mp4
51.2 MB
Part 06-Module 01-Lesson 03_Analyzing Data/17. Indexes-tSgPhxZdhLk.mp4
50.4 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/09. Other Techniques, Part 2-siuolDaB4eU.mp4
49.4 MB
Part 03-Module 01-Lesson 11_L4 Variability/32. SD Social Networkers-cy8BwWl36Q4.mp4
47.4 MB
Part 03-Module 01-Lesson 07_Google Spreadsheet Tutorial/01. Tutorial-c3yK3OhuNvo.mp4
47.3 MB
Part 06-Module 01-Lesson 03_Analyzing Data/03. Example of Aggregation Framework-pOJAW4jTjr0.mp4
46.9 MB
Part 06-Module 01-Lesson 03_Analyzing Data/18. Using Indexes-vL9FcO_9dCA.mp4
46.8 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/22. Variability Example-gs4qKb-0Lfs.mp4
46.7 MB
Part 12-Module 01-Lesson 05_Interview Practice/02. Describe your latest data project-cXluuqCVg18.mp4
44.2 MB
Part 05-Module 01-Lesson 05_Data Quality/08. Example Using our Blueprint-G3RjHqqQSgE.mp4
43.9 MB
Part 05-Module 01-Lesson 05_Data Quality/18. Auditing Uniformity-cF0AEW4SIUM.mp4
43.0 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/12. Metric Definition and Data Capture-qtVm_stSHuM.mp4
42.9 MB
Part 06-Module 01-Lesson 03_Analyzing Data/13. Group Accumulation Operators-cleAY1-Jboc.mp4
42.8 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/13. Metric Definition Example-xOSypbjALh4.mp4
42.8 MB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/06. A Problem and How You Dealt With It-7IKqdW30GvQ.mp4
42.7 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/07. Parsing XML-SIsG0HYYwY4.mp4
42.4 MB
Part 14-Module 01-Lesson 05_Analyzing Results/07. Sanity Checking Wrapup-rCAYdZk5O2E.mp4
42.2 MB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/02. Familiarize Yourself with the Dataset-JyX6j00Q2Cg.mp4
41.9 MB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/02. Familiarize Yourself with the Dataset-JyX6j00Q2Cg.mp4
41.9 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/14. Filtering and Segmenting-DETCNMqnnKw.mp4
40.6 MB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/10. Reviewing our Street Name Audit-pH3VusOq9tc.mp4
40.2 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/30. Lessons Learned, Part 2-1JRk6dgQhkE.mp4
40.2 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/25. Dot Notation-OcPW6xp8DfE.mp4
39.7 MB
Part 06-Module 01-Lesson 03_Analyzing Data/09. Project Operator-_kupbxrZBds.mp4
39.3 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/24. Empirical Variability-Wzs1KFldiUE.mp4
38.9 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/03. Unit of Diversion Example-W4Xno_vJvZM.mp4
38.5 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/16. Summary Metrics-ghMD3AfjLZc.mp4
38.0 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/03. Metric Definition Overview, Part 2-0DyLzS2ux7g.mp4
37.5 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/11. Target Population-HO1Doq8PiCI.mp4
37.4 MB
Part 06-Module 01-Lesson 03_Analyzing Data/15. Multiple Stages Using a Given Operator-0TV8kTw9-HM.mp4
37.0 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/04. Consistency of Diversion-im8-LLU5J_Y.mp4
36.7 MB
Part 11-Module 01-Lesson 06_Datasets and Questions/03. Accuracy vs. Training Set Size-9w1Yi5nMNgw.mp4
36.5 MB
Part 09-Module 01-Lesson 01_What is EDA/08. Aude Explores Coordinated Migration-7ihp6ofAJG8.mp4
36.4 MB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/08. Auditing Street Names-c0IcUiF_kXs.mp4
36.4 MB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/09. Auditing Street Names-c0IcUiF_kXs.mp4
36.4 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/03. Intro to AB Testing-ASQubLvGuxY.mp4
36.1 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/25. Empirical Variability Sanity Checking-6vxdVWIA6dI.mp4
36.0 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/03. XML Design Principles-eQpSC0IFhv0.mp4
36.0 MB
Part 14-Module 01-Lesson 05_Analyzing Results/18. Gotchas Changes Over Time-P7Hso-EoWvA.mp4
35.8 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.mp4
35.6 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.mp4
35.6 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/26. Up and Down the Visualization Spectrum-NdVf2bY8OnM.mp4
35.3 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/24. Lessons Learned-GonjL0GbNiw.mp4
34.9 MB
Part 12-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier-Uy89Ff49pRc.mp4
34.9 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/05. Refining the Customer Funnel-L2NEk4jvlcY.mp4
34.9 MB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/05. Iterating through Ways Tags-GYhOEJ8EXkg.mp4
34.3 MB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/06. Iterating through Ways Tags-GYhOEJ8EXkg.mp4
34.3 MB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/04. Meet Chris-0ccflD9x5WU.mp4
34.1 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/18. Sensitivity and Robustness-T2QI3p0yDNk.mp4
34.1 MB
Part 11-Module 01-Lesson 13_PCA/31. Eigenfaces Code-LgLYw-G4sLQ.mp4
34.0 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/02. Standard Error-GTsnxTCjmcM.mp4
33.8 MB
Part 05-Module 01-Lesson 05_Data Quality/10. Wikipedia Infobox Dataset-hpyNAYJODqw.mp4
33.7 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/05. Brainstorming-LJFYhMDCCsU.mp4
33.2 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/08. Defining Metrics Other Techniques-gEO8il9GU3M.mp4
33.1 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/19. Sensitivity and Robustness Example-_I7m7Y4hBOs.mp4
32.7 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/09. Debugging-Bz1tlvkql9Q.mp4
32.6 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/20. Duration vs. Exposure-MsByTo7FRgs.mp4
32.4 MB
Part 14-Module 01-Lesson 05_Analyzing Results/06. Checking Invariants, Part 2-05jVh4kUbHU.mp4
32.3 MB
Part 11-Module 01-Lesson 14_Validation/10. Practical Advice for K-Fold in sklearn-COVRSk0GDEE.mp4
32.0 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/12. Intro to JSON-Fi7RjhBLobY.mp4
30.3 MB
Part 13-Module 01-Lesson 07_Narrative Structures/07. How to Lie with Bar Charts-75c7a4R4pZ0.mp4
30.3 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/08. Intro to PyMongo-h6M4x9aXx5g.mp4
30.2 MB
Part 13-Module 01-Lesson 07_Narrative Structures/25. Demystifying D3-y7QK8XMHyDQ.mp4
29.9 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/02. Metric Definition Overview-pOxyL1lwBIw.mp4
29.8 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/26. Empirical Confidence Intervals-ca8GQmr7B8g.mp4
29.7 MB
Part 05-Module 01-Lesson 05_Data Quality/11. Auditing a Cross-Field Constraint-Y7TNXALXut8.mp4
29.7 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/10. Intro to XLRD-TcWtpvLSoG0.mp4
29.0 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/01. Independent Samples-K25Xtqr2WvI.mp4
29.0 MB
Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/13. Scott's Advice to Break into Data Vis-v5ywQMRCxMg.mp4
28.9 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/29. Removing Documents-oFWNOvxuIRQ.mp4
28.8 MB
Part 14-Module 01-Lesson 05_Analyzing Results/15. Multiple Metrics Example 3-XByoblkCgfE.mp4
28.8 MB
Part 14-Module 01-Lesson 05_Analyzing Results/10. Single Metric Gotchas-WrfWFLiFeMU.mp4
28.8 MB
Part 05-Module 01-Lesson 05_Data Quality/14. Auditing Accuracy 2-5xY3sCBHkOk.mp4
28.6 MB
Part 06-Module 01-Lesson 03_Analyzing Data/04. The Aggregation Pipeline-0sl_mbV-fho.mp4
28.1 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/07. History of AB Testing-NNiKGao0xnk.mp4
28.0 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/29. Formula for Location of Median-lNYLU1b4qoM.mp4
27.9 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/10. Inter- vs. Intra-User Experiments-EGE8ddtWIeo.mp4
27.4 MB
Part 14-Module 01-Lesson 05_Analyzing Results/09. Single Metric Example--QwMdwqUq9c.mp4
27.2 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/27. Set Unset-bgOky14w77Q.mp4
27.2 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/22. Simulation Applet-yu4mdXybrts.mp4
27.0 MB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/03. Iterative Parsing-pxUvIP4PQt0.mp4
27.0 MB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/03. Iterative Parsing-pxUvIP4PQt0.mp4
27.0 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/23. McDonald's-29Vf6PytVbA.mp4
26.7 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/23. McDonald's-29Vf6PytVbA.mp4
26.7 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/05. DAP Overview-qdV4sifMmWI.mp4
26.7 MB
Part 13-Module 01-Lesson 07_Narrative Structures/28. Joins in D3-rDjOINfKftY.mp4
26.6 MB
Part 05-Module 01-Lesson 05_Data Quality/15. Auditing Completeness-PMbcv9AYQT4.mp4
26.6 MB
Part 14-Module 01-Lesson 05_Analyzing Results/17. Drawing Conclusions-CZQ-nZyUG7g.mp4
26.5 MB
Part 11-Module 01-Lesson 02_Naive Bayes/01. ML in The Google Self-Driving Car-lL16AQItG1g.mp4
26.3 MB
Part 07-Module 01-Lesson 01_GitHub Review/13. Interview with Art - Part 3-M6PKr3S1rPg.mp4
26.3 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/28. Server Requests and D3-Lx9dhgMZO1s.mp4
26.2 MB
Part 18-Module 03-Lesson 01_Assessing Data/15. Quality Programatic Assessment 1-l-FhDkQRclA.mp4
26.1 MB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/09. Reviewing our Street Name Audit-eIvm5rEMZGY.mp4
25.9 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/04. Recursion-_aI2Jch6Epk.mp4
25.9 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/08. Report Results-xNbzHOnSx5Q.mp4
25.8 MB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/04. Ways in the Open Street Map XML-1OwIbj9dcLo.mp4
25.7 MB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/05. Ways in the Open Street Map XML-1OwIbj9dcLo.mp4
25.7 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/02. Case Study US Unemployment-R6Nk8NsEzUA.mp4
25.1 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/19. String Methods-Bv7CAxVOONs.mp4
24.9 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/20. Regex Operator-MbJfmI7kzQI.mp4
24.7 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/05. Fundamentals of XML-Ti8K9FmNW1w.mp4
24.6 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/15. Extracting Entities-aJD8WJa3-9A.mp4
24.5 MB
Part 11-Module 01-Lesson 09_Clustering/12. Sklearn-3zHUAXcoZ7c.mp4
24.4 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/08. Unit of Analysis vs. Unit of Diversion-rzim0wu_0kM.mp4
24.2 MB
Part 13-Module 01-Lesson 07_Narrative Structures/13. Errors in Data Collection-xcYDjXpYbs0.mp4
24.2 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/11. Other Techniques Example-z1UX9i9_piQ.mp4
24.1 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/46. World Cup Code and Narrative Recap-lnHEvGeech0.mp4
24.1 MB
Part 17-Module 01-Lesson 16_Logistic Regression/29. Model Diagnostics In Python-1Z4eorbfOOc.mp4
23.9 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/15. Filtering and Segmenting Example-WgM3cBEtkqg.mp4
23.4 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-GXT_vXBA0vQ.mp4
23.2 MB
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.mp4
23.1 MB
Part 06-Module 01-Lesson 03_Analyzing Data/06. Aggregation Operators 1-mRNyMEoCoY0.mp4
23.1 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.mp4
23.0 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/15. Filtering and Segmenting Example-XTS6m5_3fdU.mp4
23.0 MB
Part 11-Module 01-Lesson 12_Feature Selection/14. Balancing Error with Number of Features-IwiIFMcDwoA.mp4
22.9 MB
Part 07-Module 01-Lesson 01_GitHub Review/04. Interview with Art - Part 1-ClLYamtaO-Q.mp4
22.8 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/10. Boolean Comparison and Logical Operators-iNNsUJIDtVU.mp4
22.7 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/28. Multi Update-tuXc0Ycy_yM.mp4
22.6 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/04. Statistical Significance-kpdwHL54eys.mp4
22.5 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/17. Summary Metrics Example--DqU-ARfQr4.mp4
22.5 MB
Part 14-Module 01-Lesson 05_Analyzing Results/13. Multiple Metrics Example-60IGcSho56o.mp4
22.4 MB
Part 14-Module 01-Lesson 05_Analyzing Results/19. Lessons Learned-5JjCVTc0FGk.mp4
22.2 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-AqlvTMZg6HY.mp4
22.1 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/06. Flexible Schema-6a-YgbrEACk.mp4
22.1 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-qsWz7r8muII.mp4
22.1 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-74mudn321tA.mp4
22.0 MB
Part 09-Module 01-Lesson 01_What is EDA/03. Why learn EDA-YM68DrqJw1I.mp4
22.0 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/08. Whitespace-UxkIwcOczQQ.mp4
22.0 MB
Part 14-Module 01-Lesson 05_Analyzing Results/02. Sanity Checks-OVnlC_T3EpI.mp4
22.0 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/26. Klout-3q0oPuWxFpA.mp4
21.9 MB
Part 11-Module 01-Lesson 13_PCA/28. PCA in sklearn-SBYdqlLgbGk.mp4
21.9 MB
Part 11-Module 01-Lesson 13_PCA/23. PCA for Feature Transformation-8kUPRUEMCA8.mp4
21.8 MB
Part 12-Module 02-Lesson 02_List-Based Collections/11. Queues-XAbzlilAHZw.mp4
21.7 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-O9d9dKyHtIc.mp4
21.7 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/15. SD of Karma Points per Post-uCRzrlaA8mg.mp4
21.6 MB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/02. Elevator Pitch-S-nAHPrkQrQ.mp4
21.6 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/19. Between 10 and 16-4QIEdzv6g6w.mp4
21.6 MB
Part 03-Module 01-Lesson 20_L8 Estimation/23. CI Bounds-6MdZ5NUfen0.mp4
21.6 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/20. How Scales Work-4zqm8dz7Z-k.mp4
21.5 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/06. Critical Regions-UF3japjNx98.mp4
21.4 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/31. Layout and Scales-BQWN9ImjUFE.mp4
21.3 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size-MLzRdgcFYQQ.mp4
21.3 MB
Part 12-Module 01-Lesson 05_Interview Practice/07. Jimmy's Analysis of the Interview-wg535YU4jFw.mp4
21.3 MB
Part 11-Module 01-Lesson 02_Naive Bayes/18. Gaussian NB Example-wpnDwiqTCJA.mp4
21.3 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/17. Range Queries-6r5Xc-_lhEI.mp4
21.2 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.mp4
21.1 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.mp4
21.1 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/04. David's Data Wrangling Example-TN-CWy3GK44.mp4
21.0 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/10. Techniques to Gather Additional Data-6mTsvU0ML94.mp4
21.0 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-ycbXO4xBEVw.mp4
21.0 MB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/10. Welcome to the end of the lesson-nWFJ_eOU27I.mp4
20.9 MB
Part 21-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.mp4
20.9 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/06. Intro to Sorting-Z6yuIen71zM.mp4
20.9 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/23. Nonparametric Answers-Z0QcZHrflmc.mp4
20.7 MB
Part 03-Module 01-Lesson 20_L8 Estimation/19. Engagement Ratio-EdIcXVIYX88.mp4
20.7 MB
Part 03-Module 01-Lesson 20_L8 Estimation/10. 95 CI with Exact Z-Scores-apqUAtnsLZE.mp4
20.5 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/17. More Work Than We Thought-vgJ0ZlxzSiw.mp4
20.5 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/02. Data Modeling in MongoDB-6sDkIE_nAGI.mp4
20.4 MB
Part 11-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-GdsLRKjjKLw.mp4
20.3 MB
Part 11-Module 01-Lesson 14_Validation/09. K-Fold CV in sklearn-QSYMwFbE7PA.mp4
20.2 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/14. Helpful Symbols-w4_8YCp-9fI.mp4
20.1 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/26. Updates-mpMHJQalRck.mp4
20.0 MB
Part 11-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.mp4
20.0 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/14. Population vs. Cohort Example-MXukXfzL59E.mp4
20.0 MB
Part 18-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 Solution-CWJZoi_Es84.mp4
19.9 MB
Part 14-Module 01-Lesson 05_Analyzing Results/14. Multiple Metrics Example 2-nTeQi9MjgiA.mp4
19.9 MB
Part 21-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.mp4
19.9 MB
Part 09-Module 02-Lesson 01_Explore and Summarize Data/06. Explore And Summarize Data Walkthrough Final-_OwKKL6SI38.mp4
19.8 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/20. Practical, or Substantive, Significance-Q576t5aaZ34.mp4
19.8 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/07. What is a Projection-QjVNXfI8YRk.mp4
19.8 MB
Part 14-Module 01-Lesson 05_Analyzing Results/08. Single Metric Introduction-StP9L9f70EU.mp4
19.8 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/06. CSV Format-ra93hy88cok.mp4
19.8 MB
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/03. Digging deeper with Trina-i9xslfFp80g.mp4
19.7 MB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/05. Tableau Dashboards Stories with Trina-i9xslfFp80g.mp4
19.7 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/25. Smoothing Conditional Means-hxk2cgdChUw.mp4
19.7 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/01. t-Distribution-N6wKbV1DVos.mp4
19.7 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/02. Unit of Diversion Overview-Gh32VbXrmdQ.mp4
19.7 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/07. DF - Sample SD-Jfk3egev9UM.mp4
19.7 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/06. Choosing Metrics-eAukkpVFl5c.mp4
19.7 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/04. NumPy Arrays-7GeiZ8IVZfE.mp4
19.7 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/05. NumPy Arrays-7GeiZ8IVZfE.mp4
19.7 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/04. Load D3 in the JavaScript Console-mGyo6dOf0So.mp4
19.5 MB
Part 14-Module 01-Lesson 05_Analyzing Results/03. Choosing Invariants-E1ePfjcVH3I.mp4
19.5 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/12. Target Population Example-XsyavvSGjLM.mp4
19.5 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/13. Population vs. Cohort-HC2dunMuVW4.mp4
19.4 MB
Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI-L_JV4fbRAfA.mp4
19.4 MB
Part 21-Module 01-Lesson 03_Control Flow/10. For Loops-UtX0PXSUCdY.mp4
19.3 MB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/07. Efficiency-I-RASDPbDrI.mp4
19.3 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/05. How Does MLR Work-bvM6eUYyurA.mp4
19.3 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/20. Absolute or Relative Difference-TNcT_v2g3OQ.mp4
19.3 MB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/08. Time When You Dealt With Failure-Qb4o_4hCuyg.mp4
19.3 MB
Part 12-Module 01-Lesson 03_Interview Fails/03. Interviewing Fails Siya Raj Purohit-wYop-N5YgeA.mp4
19.3 MB
Part 09-Module 01-Lesson 03_Explore One Variable/21. Lada's Money Bag Meme-Isa_FGQrvgs.mp4
19.2 MB
Part 14-Module 01-Lesson 05_Analyzing Results/11. Gotchas Simpson’s Paradox-GSPTcqNpab8.mp4
19.2 MB
Part 21-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.mp4
19.2 MB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/05. Writing the Body-aK9Qnv3a6Wg.mp4
19.1 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/16. Sizing Overview-sKRWt_iS7zo.mp4
19.0 MB
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-spVqFnSvlIU.mp4
19.0 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-hmhlyOVAVOs.mp4
19.0 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/06. Other Techniques-KsiyW6bPux8.mp4
18.9 MB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.mp4
18.9 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/11. Other Techniques Example-sOGuF3it6Ek.mp4
18.9 MB
Part 05-Module 01-Lesson 05_Data Quality/07. A Blueprint for Cleaning-3S73cNbhuAk.mp4
18.7 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-gfuknvEP2ro.mp4
18.7 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/01. Welcome to the DA Nanodegree Program-FKcIJkTA3GI.mp4
18.5 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/02. Intro to XML-eIVifBVJQIw.mp4
18.5 MB
Part 11-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary-gBwGPI0srBE.mp4
18.5 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5-tEmdl6zhvgA.mp4
18.4 MB
Part 11-Module 01-Lesson 13_PCA/29. When to Use PCA-hJZHcmJBk1o.mp4
18.4 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/17. Multicollinearity VIFs-wbtrXMusDe8.mp4
18.4 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/03. Good Data Visualization-ePekYbKs60U.mp4
18.3 MB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.mp4
18.2 MB
Part 21-Module 01-Lesson 03_Control Flow/31. List Comprehensions-6qxo-NV9v_s.mp4
18.2 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/15. Using mongoimport-JVYH9B6Obpg.mp4
18.2 MB
Part 11-Module 01-Lesson 06_Datasets and Questions/04. Downloading Enron Data-TgkBAtaTqJk.mp4
18.2 MB
Part 13-Module 01-Lesson 07_Narrative Structures/11. Personal Data Visualization-NtFICAw7tW4.mp4
18.2 MB
Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-4GBJk6R0pb4.mp4
18.2 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/22. Interactions Higher Order Terms-gMHwogzqPOk.mp4
18.1 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/11. Subquery Solution Video-Y6S3S0LsMrw.mp4
18.1 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/06. Interpreting Multiplie Linear Regression Coefficients-qRD3OVX8UMM.mp4
18.1 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/13. Strings-ySZDrs-nNqg.mp4
18.1 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/27. Empirical Variability Bootstrapping-YW-uud_btQ8.mp4
18.1 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/28. Assumptions-CdoWdNAKSYw.mp4
18.0 MB
Part 21-Module 01-Lesson 03_Control Flow/02. If Statements-jWiIUMrwPqA.mp4
17.8 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-qgwygpD0eN8.mp4
17.8 MB
Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-Hb2q-o4ElV4.mp4
17.8 MB
Part 03-Module 01-Lesson 11_L4 Variability/24. Formula for Avg. Abs. Dev.-ihC1Pm8E8gU.mp4
17.8 MB
Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-krV6r7HxmZU.mp4
17.8 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/26. Confidence Interval Case Breakdown-6pGDwrJHitw.mp4
17.7 MB
Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.mp4
17.7 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.mp4
17.6 MB
Part 11-Module 01-Lesson 12_Feature Selection/15. Regularization-l9V5tlIWTvs.mp4
17.6 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/15. Finches-ONhDQKYCJlE.mp4
17.6 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.mp4
17.6 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.mp4
17.6 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question-XvvKBmKC_84.mp4
17.5 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/13. Where's the Data-rHQ8z4fIthA.mp4
17.5 MB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/01. Get an Interview with a Cover Letter!-BH1KY63YfAM.mp4
17.5 MB
Part 11-Module 01-Lesson 11_Text Learning/06. Bag of Words in Sklearn-aCdg-d_476Y.mp4
17.5 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/13. Binomial Distribution-nXbucNJpP8I.mp4
17.4 MB
Part 06-Module 01-Lesson 03_Analyzing Data/08. Match Operator-FZ8KVv1VOK4.mp4
17.4 MB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.mp4
17.4 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/21. Variability-1KmFcGt6Uo0.mp4
17.4 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/01. Intro-UJyJm79RS88.mp4
17.3 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/11. Efficiency of Merge Sort-HKiK5Y-YSkk.mp4
17.3 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/19. Sizing Triggering-ae9SWJxGM0w.mp4
17.3 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-EtWewV65zbs.mp4
17.1 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/19. Exists-j5l5UvE3Odw.mp4
17.0 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/08. Dummy Variables--QTgDd-fZuA.mp4
17.0 MB
Part 12-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-R9AtVBq2Z5E.mp4
16.9 MB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/04. Time When You Showed Initiative-29mkriaGT0E.mp4
16.9 MB
Part 06-Module 01-Lesson 03_Analyzing Data/02. Twitter Data Set-xiqleK_px_Q.mp4
16.9 MB
Part 11-Module 01-Lesson 14_Validation/03. TrainTest Split in sklearn-lSwvUmZCvco.mp4
16.9 MB
Part 14-Module 01-Lesson 05_Analyzing Results/11. Gotchas Simpson’s Paradox-Tx_jtCfrbt0.mp4
16.7 MB
Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-jkJ4dbbpVCQ.mp4
16.7 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.mp4
16.7 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/09. Questions and Consent-ZmXg42IoG_Q.mp4
16.7 MB
Part 18-Module 02-Lesson 01_Gathering Data/10. HTML Files in Python 1-0VZumC18UvQ.mp4
16.7 MB
Part 21-Module 01-Lesson 04_Functions/08. Documentation-_Vl9NJkA6JQ.mp4
16.7 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/48. Matt's Tips for Making Maps-HCYCT2TXhAM.mp4
16.7 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-xsdj1qJwgk4.mp4
16.7 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/06. DF - Marginal Totals-PBcd_dxiFbE.mp4
16.7 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/15. Calculating a Confidence Interval-HGYW-skXvY4.mp4
16.7 MB
Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.mp4
16.6 MB
Part 21-Module 01-Lesson 03_Control Flow/28. Zip and Enumerate-bSJPzVArE7M.mp4
16.5 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/15. Different Bin Sizes-_wOXWBZkL58.mp4
16.4 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/31. What Do You Get with a Good Klout Score-7N7MBPJKCfw.mp4
16.4 MB
Part 11-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter-m2a2K4lprQw.mp4
16.3 MB
Part 21-Module 01-Lesson 04_Functions/02. Defining Functions-IP_tJYhynbc.mp4
16.2 MB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/18. 39. SAD-tya_avP-hKc.mp4
16.2 MB
Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5DvUOwA7xhU.mp4
16.2 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/08. Números inteiros e floats-MiJ1vfWp-Ts.mp4
16.2 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.mp4
16.1 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.mp4
16.1 MB
Part 09-Module 01-Lesson 02_R Basics/04. Install RStudio on Windows-5ZbjUEg4a1g.mp4
16.1 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-9JfaMZcSlQA.mp4
16.0 MB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/01. Course Introduction-NKBUbUiedzc.mp4
16.0 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/17. Z-Score-pftNHu4uevA.mp4
16.0 MB
Part 11-Module 01-Lesson 02_Naive Bayes/36. Naive Bayes Strengths and Weaknesses-nfbKTrufPOs.mp4
15.9 MB
Part 03-Module 01-Lesson 20_L8 Estimation/01. Summary-51hx5u2EMZA.mp4
15.9 MB
Part 18-Module 04-Lesson 01_Cleaning Data/17. Flashforward-rfMu3f9O9hQ.mp4
15.9 MB
Part 13-Module 01-Lesson 04_Design Principles/47. Discovery versus Presentation-znQ3iBhhJtA.mp4
15.8 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/22. Scraping Solution-J1gn4ZBLkt4.mp4
15.8 MB
Part 05-Module 01-Lesson 05_Data Quality/17. Consistency-_5AnMdslWg4.mp4
15.8 MB
Part 21-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.mp4
15.8 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/32. What Happened-NSuT87J4V-g.mp4
15.8 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/14. Procedure-6rSJRr9OtHM.mp4
15.7 MB
Part 12-Module 01-Lesson 01_Ace Your Interview/02. Interviewing Conversations-klqXp09Pen4.mp4
15.7 MB
Part 13-Module 01-Lesson 04_Design Principles/22. Encoding Nothing-6bpET1lWVtA.mp4
15.7 MB
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.mp4
15.7 MB
Part 13-Module 01-Lesson 07_Narrative Structures/56. Recap and Data Dependency-00Tz_3_91RU.mp4
15.7 MB
Part 11-Module 01-Lesson 10_Feature Scaling/11. MinMax Scaler in sklearn-lgoh5R05YM0.mp4
15.6 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/01. Introduction-yod62-mxXR4.mp4
15.6 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/12. DataFrame apply()-KSZ2XLYk4hk.mp4
15.6 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/12. DataFrame apply()-KSZ2XLYk4hk.mp4
15.6 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.mp4
15.5 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.mp4
15.5 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/01. Binary Search-0VN5iwEyq4c.mp4
15.4 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/16. Mean Number of Shoes-j3RQ-8l2nos.mp4
15.3 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/24. MM CLT-IAVgtiZLlOg.mp4
15.3 MB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/01. Introduction-ICKBWIkfeJ8.mp4
15.3 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/10. Merge Sort-K916wfSzKxE.mp4
15.3 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces--VxKwVvrNY0.mp4
15.3 MB
Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces--VxKwVvrNY0.mp4
15.3 MB
Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-YbVuN2KOlt4.mp4
15.3 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/04. Why MongoDB-jjMw4Ju-1CM.mp4
15.2 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-w6CLWh1dLCU.mp4
15.2 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-9piyE5in7YE.mp4
15.2 MB
Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-FDSmlIBy7ko.mp4
15.1 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/15. Potential Problems-lGwB6YRThbI.mp4
15.1 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/18. Combining Pandas DataFrames-_Rx9Z-uURQk.mp4
15.1 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/18. Combining Pandas DataFrames-_Rx9Z-uURQk.mp4
15.1 MB
Part 12-Module 02-Lesson 02_List-Based Collections/09. Stacks Details-HpaVHzDeZC4.mp4
15.1 MB
Part 03-Module 01-Lesson 11_L4 Variability/35. Point of SD-d-_ZKyocTDw.mp4
15.1 MB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/04. Writing Your Introduction-5S5PH73WLLY.mp4
15.1 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/29. Decision Errors-4QMqg8izUac.mp4
15.1 MB
Part 13-Module 01-Lesson 07_Narrative Structures/19. Viewer-driven Examples-ft07qc8rTwM.mp4
15.0 MB
Part 13-Module 01-Lesson 07_Narrative Structures/04. The New Journalism-ub1_Gwc6wN8.mp4
15.0 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/11. Z-Table-hSAxcGBxbds.mp4
15.0 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-ljBJOXJTR9A.mp4
15.0 MB
Part 12-Module 02-Lesson 02_List-Based Collections/05. Linked Lists-zxkpZrozDUk.mp4
15.0 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/20. Broken Requests-QFjKVSmxODY.mp4
15.0 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/30. Rent - Increase n-UUn6ETq08SU.mp4
14.9 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/16. Data Types-ZqRIS9etBqY.mp4
14.9 MB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/04. Data Types - Data Visualization and D3.js-ZqRIS9etBqY.mp4
14.9 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.mp4
14.9 MB
Part 13-Module 01-Lesson 07_Narrative Structures/46. Inspecting Data with Functions--itFNdnc5ns.mp4
14.8 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/41. Types of Designs-IcrYt7Tzccg.mp4
14.8 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/12. Projection Queries-dFGlIC9nI1Q.mp4
14.8 MB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/14. What is plot.ly-ZRiAWz-sVlM.mp4
14.7 MB
Part 12-Module 01-Lesson 03_Interview Fails/02. Interviewing Fails Mike Wales-OGXRmzBglI4.mp4
14.7 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/15. Hypotheses-DepOzUJw_bQ.mp4
14.7 MB
Part 11-Module 01-Lesson 07_Regressions/19. Extracting Information from sklearn-zDIRQE_oxfk.mp4
14.6 MB
Part 14-Module 01-Lesson 05_Analyzing Results/12. Multiple Metrics Introduction-dw0UylGwPe8.mp4
14.6 MB
Part 18-Module 03-Lesson 01_Assessing Data/09. Quality Visual Assessment 1 -XfKc5PtJ7cc.mp4
14.6 MB
Part 13-Module 01-Lesson 04_Design Principles/14. Common and Less Common Charts on plot.ly-V9xxdiwJtWk.mp4
14.5 MB
Part 15-Module 01-Lesson 02_Design Principles/06. Gráficos Comuns e Menos Comuns no plot.ly-V9xxdiwJtWk.mp4
14.5 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/23. Pooled Variance Sum of Squares-H-1atcURVzk.mp4
14.5 MB
Part 05-Module 01-Lesson 05_Data Quality/05. Measuring Data Quality-dj46LqDBFYM.mp4
14.5 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/03. Facebook Experiment-VqLX0wnrldc.mp4
14.5 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/02. Multiple Linear Regression-rvYZp99nj6c.mp4
14.5 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/31. Dependent Samples-kcTh3hJ1XCw.mp4
14.4 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/06. Words of Wisdom from Zipfian Academy-ani9_ZalK-8.mp4
14.4 MB
Part 08-Module 01-Lesson 01_Conduct a Job Search/03. Target Your Application to An Employer-X9JBzbrkcvs.mp4
14.4 MB
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-7CVlKQ3UjUI.mp4
14.4 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/11. Two-Tailed Test-VFS9mGdkU-M.mp4
14.4 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/23. The Facebook Offering-ORLP-phGXMU.mp4
14.3 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/24. MM CLT-DqC-pgcEam4.mp4
14.3 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/38. Something Fun-7kOZs5PLtqs.mp4
14.3 MB
Part 18-Module 03-Lesson 01_Assessing Data/03. Dataset Oral Insulin Clinical Trial Data-R-HT78SPxpE.mp4
14.3 MB
Part 18-Module 04-Lesson 01_Cleaning Data/03. Dataset Oral Insulin Clinical Trial Data -R-HT78SPxpE.mp4
14.3 MB
Part 03-Module 01-Lesson 20_L8 Estimation/18. Critical Values of Z-_vKCQnll45c.mp4
14.3 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score-1V7JzqCfe9o.mp4
14.1 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-fo4MJMkwhYU.mp4
14.1 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.mp4
14.1 MB
Part 11-Module 01-Lesson 07_Regressions/27. Problem with Minimizing Absolute Errors-U46D7oEijlI.mp4
14.0 MB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.mp4
14.0 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/11. Dummy Variable Interpretation-TxP_TD0kbOo.mp4
14.0 MB
Part 11-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye-sJgPnuiHrs8.mp4
14.0 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/18. Visual Encodings-14FJU1kP6-M.mp4
14.0 MB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/07. Visual Encodings - Data Visualization and D3.js-14FJU1kP6-M.mp4
14.0 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/25. L2 06 Lists Methods V1-tz2Ja1Eaeqo.mp4
14.0 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/13. Binomial Distribution-PVTChqpnr5Q.mp4
14.0 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/02. Tuskegee and Milgram Experiments-mxNp8_3syVk.mp4
14.0 MB
Part 11-Module 01-Lesson 04_Decision Trees/34. DT Strengths and Weaknesses-KGnhg76iRfI.mp4
13.9 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.mp4
13.9 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/13. One-Sample t-Test-IdP9Ps2tHgw.mp4
13.9 MB
Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-hfmvk8DzTGA.mp4
13.9 MB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components-AiFcaHRGdEA.mp4
13.9 MB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components-AiFcaHRGdEA.mp4
13.9 MB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components-AiFcaHRGdEA.mp4
13.9 MB
Part 21-Module 01-Lesson 03_Control Flow/25. Break and Continue-F6qJAv9ts9Y.mp4
13.9 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/29. Collecting Participating Countries-ha6kGtT9XMQ.mp4
13.9 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5-ONwh_Dcd6j8.mp4
13.9 MB
Part 07-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2-Vvzl2J5K7-Y.mp4
13.8 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-0XM5ILuCg1k.mp4
13.8 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/32. Binding Data-yW9LEMFOzgY.mp4
13.8 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/08. Calculating Correlation-isBv5D88Nso.mp4
13.7 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/08. Calculating Correlation-isBv5D88Nso.mp4
13.7 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/12. Target Population Example-kEFp6xIb8cs.mp4
13.7 MB
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/02. Exploring data with Trina-sLzULEjMY1E.mp4
13.7 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/13. Metric Definition Example-1EoJTK_S0mk.mp4
13.6 MB
Part 18-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 1-nDWAZOU3W3U.mp4
13.6 MB
Part 14-Module 01-Lesson 05_Analyzing Results/13. Multiple Metrics Example-0eCWo0h5DpM.mp4
13.6 MB
Part 03-Module 01-Lesson 20_L8 Estimation/06. Interval Estimate for Population Mean-ECRw3cSiy6o.mp4
13.6 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.mp4
13.6 MB
Part 11-Module 01-Lesson 06_Datasets and Questions/02. What Is A POI-wDQhif-MWuY.mp4
13.5 MB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/06. Resume Review-L3F2BFGYMtI.mp4
13.5 MB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/06. Resume Review-L3F2BFGYMtI.mp4
13.5 MB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/06. Resume Review-L3F2BFGYMtI.mp4
13.5 MB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.mp4
13.5 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/22. How Page Views Affect Sensitivity-WFVj8QI_uto.mp4
13.4 MB
Part 21-Module 01-Lesson 03_Control Flow/07. Truth Value Testing-e52uw7ejV8k.mp4
13.4 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/08. Darts-fSj1dwh7Kxc.mp4
13.4 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/02. Problems Solved by Data Analysts-jZEbCVZzwUk.mp4
13.4 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/01. Intro to MongoDB-GfK7GW3V-W0.mp4
13.4 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/01. What is Data Visualization-mfLklbVU7r0.mp4
13.3 MB
Part 11-Module 01-Lesson 09_Clustering/01. Unsupervised Learning-Mx9f99bRB3Q.mp4
13.3 MB
Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-wPI9WOfpZbM.mp4
13.3 MB
Part 03-Module 01-Lesson 11_L4 Variability/16. Measure Variability-g_V6OCICUUc.mp4
13.3 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/03. Data Analysis Process-cAceF0h4vpI.mp4
13.3 MB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/05. Resume Reflection-8Cj_tCp8mls.mp4
13.3 MB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection-8Cj_tCp8mls.mp4
13.3 MB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection-8Cj_tCp8mls.mp4
13.3 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/32. What Happened-vD9iXeq3PKc.mp4
13.2 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score-6kdmc3iTf78.mp4
13.2 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.mp4
13.2 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-VUfaXWrr3oY.mp4
13.2 MB
Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.mp4
13.1 MB
Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-NjuenhkC-44.mp4
13.1 MB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/07. What Do You Know About the Company-CcTfHemUvbM.mp4
13.1 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/23. MMs-nCwZE4n4FAs.mp4
13.1 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/10. Two-Tailed Critical Values 0.05-X5GWgtZEsgc.mp4
13.1 MB
Part 13-Module 01-Lesson 04_Design Principles/19. Pre-attentive Attributes-6UvLbIX0NQ4.mp4
13.0 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-8zWQmAVPthY.mp4
13.0 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/13. Pandas Series-8zWQmAVPthY.mp4
13.0 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-O0zo3-NtBSI.mp4
13.0 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-O0zo3-NtBSI.mp4
13.0 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/01. Welcome!-KJT4Z0xpHns.mp4
13.0 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-mIBKd-JBnXY.mp4
12.9 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/02. Alpha Levels-pjBOYFAkNME.mp4
12.9 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/13. Thematic Maps-Jw2q-B2kM9k.mp4
12.8 MB
Part 12-Module 02-Lesson 04_Maps and Hashing/04. Introduction to Hashing-8yik3RlDFgM.mp4
12.8 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/11. Introducing the Working Example-ax7aaLNZkPA.mp4
12.8 MB
Part 13-Module 01-Lesson 05_Dimple.js/12. Creating and Drawing the Chart-ZyhYNaRqqL0.mp4
12.8 MB
Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-OurfO1ZR2GU.mp4
12.8 MB
Part 11-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.mp4
12.8 MB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/03. Resume Structure-POM0MqLTj98.mp4
12.8 MB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/03. Resume Structure-POM0MqLTj98.mp4
12.8 MB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/03. Resume Structure-POM0MqLTj98.mp4
12.8 MB
Part 13-Module 01-Lesson 07_Narrative Structures/21. Drone Strikes and Gun Deaths-_MXW29cfh_8.mp4
12.8 MB
Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-4hoT_su75AQ.mp4
12.7 MB
Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-oEhevl5DWpk.mp4
12.7 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-UkGwgerJU44.mp4
12.7 MB
Part 13-Module 01-Lesson 07_Narrative Structures/05. The Difficulty of Data Visualization-xzo96P5BwSI.mp4
12.7 MB
Part 08-Module 01-Lesson 01_Conduct a Job Search/02. Job Search Mindset-cBk7bno3KS0.mp4
12.7 MB
Part 11-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data-x2dmBUEKQIA.mp4
12.6 MB
Part 11-Module 01-Lesson 07_Regressions/31. R Squared in SKlearn-Dxf1I4IE6co.mp4
12.6 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/05. Lets Make a Map-mOZuq2JoN-k.mp4
12.6 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.mp4
12.6 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/23. Measures of Center-eNoE9hSDxPA.mp4
12.6 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/02. Efficiency of Binary Search-7WbRB7dSyvc.mp4
12.5 MB
Part 03-Module 01-Lesson 20_L8 Estimation/20. Hypothesis Testing Song-ER5AITzr77g.mp4
12.5 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/27. What If Our Sample Is Large-WoTCeSTL1eM.mp4
12.5 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.mp4
12.5 MB
Part 03-Module 01-Lesson 20_L8 Estimation/15. Bigger Sample, Smaller CI-DRarpjC23kc.mp4
12.5 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/26. Adding and Formatting China's Red Dot-qgTSR_ggTDg.mp4
12.5 MB
Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-x-8-2zy8gmI.mp4
12.5 MB
Part 12-Module 02-Lesson 02_List-Based Collections/01. Welcome to Collections-cZORvZq-tI0.mp4
12.4 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/06. Choosing Metrics-mOH45PzylKk.mp4
12.4 MB
Part 03-Module 01-Lesson 11_L4 Variability/10. IQR-d7J0y_PSP2I.mp4
12.4 MB
Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-NvgWKf-iBsw.mp4
12.4 MB
Part 13-Module 01-Lesson 07_Narrative Structures/36. Circles with Bound __data__-JeJ_glcExUs.mp4
12.4 MB
Part 03-Module 01-Lesson 20_L8 Estimation/25. Margin of Error-slBW5Neh2cs.mp4
12.4 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. More on Performance Tuning-ZK1FvNH10Ag.mp4
12.4 MB
Part 11-Module 01-Lesson 12_Feature Selection/16. Lasso Regression-qU1_cj4LfLY.mp4
12.3 MB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-IwcoGtFuYSo.mp4
12.3 MB
Part 03-Module 01-Lesson 11_L4 Variability/39. Clarifying Sample SD-iRudjk53deY.mp4
12.2 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-MV_e0z9kFjM.mp4
12.2 MB
Part 09-Module 01-Lesson 01_What is EDA/04. Aude's Interest in Data-DDNSMG_RltY.mp4
12.2 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-JqyUT7RbvgI.mp4
12.1 MB
Part 17-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.mp4
12.1 MB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.mp4
12.1 MB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.mp4
12.1 MB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.mp4
12.1 MB
Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-tfYAGBIR_Ws.mp4
12.1 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-EwV5Vs2m33w.mp4
12.1 MB
Part 11-Module 01-Lesson 10_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.mp4
12.1 MB
Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size-rS6udGwrN90.mp4
12.1 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/06. Ethical Considerations for Diversion-Zf0XzYNsado.mp4
12.1 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/22. Find P-Value-TVN4JfSm144.mp4
12.1 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/09. Types Of Errors - Part II-mbdSQ5CjdFs.mp4
12.0 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/21. Sampling Observations-PsRMReOqccg.mp4
12.0 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/11. Bounds of Area-UPRiS4xRnow.mp4
12.0 MB
Part 05-Module 02-Lesson 01_Data and Tables/01. Intro to SQL for Data Analysis-CU4igXr9xTw.mp4
12.0 MB
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.mp4
12.0 MB
Part 18-Module 02-Lesson 01_Gathering Data/10. HTML Files In Python 2-3caDGTxcoCw.mp4
12.0 MB
Part 18-Module 03-Lesson 01_Assessing Data/12. Data Quality Dimensions 1-5UYGvKDsd-M.mp4
12.0 MB
Part 21-Module 01-Lesson 05_Scripting/20. Importing Files-qjeSn6zZbR0.mp4
12.0 MB
Part 03-Module 01-Lesson 20_L8 Estimation/12. Generalize CI-7JS9PPQ6cN4.mp4
12.0 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/22. in Operator-8iX-7hwKX1Q.mp4
11.9 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-QoEqPotgMbA.mp4
11.9 MB
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.mp4
11.9 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/18. Multicollinearity VIFs-uiF3UcDWwPI.mp4
11.9 MB
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-BngCW1fjvFk.mp4
11.8 MB
Part 17-Module 01-Lesson 16_Logistic Regression/06. Interpreting Results-UPOxxbKu6CQ.mp4
11.8 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/08. Infinitely Small-9ftDJRsfEUI.mp4
11.8 MB
Part 17-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.mp4
11.8 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/17. Sizing Example-f69Hs7m1axc.mp4
11.8 MB
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.mp4
11.8 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/12. One-Sample t-Test-QyjjSIvJ_F4.mp4
11.7 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.mp4
11.7 MB
Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250-mPcWDYTRDs8.mp4
11.7 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/02. Defining Data Visualization-TMH43G11OnQ.mp4
11.7 MB
Part 14-Module 01-Lesson 05_Analyzing Results/14. Multiple Metrics Example 2-m0E26ndQBNo.mp4
11.7 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-vuu3BY7X9ps.mp4
11.7 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys-fnbLMcd0FGQ.mp4
11.6 MB
Part 13-Module 01-Lesson 04_Design Principles/29. Correcting Color-7vaHp4caWxw.mp4
11.6 MB
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-NXbR9GQbtnk.mp4
11.6 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/02. Arithmetic Operators-M8TIOK2P2yw.mp4
11.6 MB
Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.mp4
11.6 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess-XoQr2hohdvI.mp4
11.6 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/17. Collecting Stadium Locations-CqE3Zqv21Wo.mp4
11.6 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-KYa8_fuZ30w.mp4
11.5 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size-4-MF0UZac8o.mp4
11.5 MB
Part 06-Module 01-Lesson 03_Analyzing Data/07. Aggregation Operators 2-UZMklqP5-p4.mp4
11.5 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/11. Z-1MZnEo0UVX4.mp4
11.5 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.mp4
11.5 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-WkInrWZwbNA.mp4
11.5 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.mp4
11.5 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.mp4
11.5 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose-pBSQI8EmhvM.mp4
11.5 MB
Part 17-Module 01-Lesson 16_Logistic Regression/07. Interpreting Results in Python-IY88UTiJltQ.mp4
11.5 MB
Part 05-Module 02-Lesson 01_Data and Tables/12. Related Tables-lMwSjDYgCq0.mp4
11.5 MB
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.mp4
11.5 MB
Part 21-Module 01-Lesson 03_Control Flow/20. L3 08 While Loops V3-7Sf5tcPlKQw.mp4
11.4 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/10. Estimating Click-Through-Probability-Hkbc_vcb7D8.mp4
11.4 MB
Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-paj5z9U1OBk.mp4
11.3 MB
Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.mp4
11.3 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/11. D3 Chain Syntax and Changing the Navbar-DQ9_HknCsAI.mp4
11.3 MB
Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files-w-ZG6DMkVi4.mp4
11.3 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/14. Common Types of Hypothesis Tests-8hv8KnvQ6JY.mp4
11.3 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-4Aj_qdImmGo.mp4
11.3 MB
Part 17-Module 01-Lesson 16_Logistic Regression/01. Introduction to Logistic Regression-P_f2RjjnPEg.mp4
11.3 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/17. Exploring Student Engagement-6QLiscx_zIY.mp4
11.3 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/12. Affect t-Statistic-c6vE21UVksU.mp4
11.3 MB
Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-v4UGBUB6jO4.mp4
11.3 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/19. Checking the Nest Return-hCXhsYVLqig.mp4
11.3 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/09. SQL Subquery Video-10pmKmTI_CA.mp4
11.3 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.mp4
11.3 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/16. Beginning to Build Our http Requests-ojd7xXOd_64.mp4
11.3 MB
Part 12-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability-pDELcPTP2BI.mp4
11.2 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/31. L2 02 Dictionaries And Identiy Operators V3-QR8HTxCTWi0.mp4
11.2 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-Hs3__UsSyL8.mp4
11.2 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/02. Hypothesis Testing-9GbHHpiK6wk.mp4
11.2 MB
Part 11-Module 01-Lesson 16_Tying It All Together/04. Outro-VCNcNnZ6V_s.mp4
11.2 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.mp4
11.2 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.mp4
11.2 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/14. The Central Limit Theorem-ag3TB5UGu_g.mp4
11.2 MB
Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.mp4
11.2 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample-9na_mOWP7pw.mp4
11.1 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/18. Better Sample-9na_mOWP7pw.mp4
11.1 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/27. Empirical Variability Bootstrapping-FvtAeWdzy4k.mp4
11.1 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/22. Conduct Hypothesis Test-HTuI3iFzOdU.mp4
11.1 MB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/02. Data Has Dimensions-F4NSv776X0c.mp4
11.1 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/17. Cleaning Example-7bnSPYtPDzQ.mp4
11.1 MB
Part 21-Module 01-Lesson 05_Scripting/21. The Standard Library-Fw3vf0tDrJM.mp4
11.1 MB
Part 11-Module 01-Lesson 09_Clustering/10. K-Means Clustering Visualization 2-fQXXa-CAoS0.mp4
11.0 MB
Part 03-Module 01-Lesson 11_L4 Variability/26. Sum of Squares-fktfjG1SnkI.mp4
11.0 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure-CfDLpojt4AY.mp4
11.0 MB
Part 03-Module 01-Lesson 11_L4 Variability/12. Define Outlier-7rLkGwsbMUY.mp4
11.0 MB
Part 13-Module 01-Lesson 04_Design Principles/13. Additional Chart Types-4G-KhrIDqGA.mp4
11.0 MB
Part 13-Module 01-Lesson 04_Design Principles/06. Common Chart Types-xD2_AU6atqA.mp4
11.0 MB
Part 15-Module 01-Lesson 02_Design Principles/02. Tipos Comuns de Gráficos-xD2_AU6atqA.mp4
11.0 MB
Part 08-Module 01-Lesson 01_Conduct a Job Search/01. Introduction-axcFtHK6If4.mp4
11.0 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/12. Using the Z-Table-GF0qAvNKpOA.mp4
10.9 MB
Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error-FpeMuGuo74k.mp4
10.9 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-f1fz9cLnetM.mp4
10.9 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots-GmR3uEM189M.mp4
10.9 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-f7vNKm0Zci0.mp4
10.9 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/23. Interpreting Interactions-XV6S2srsdxw.mp4
10.9 MB
Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds-WeS0ogG86nk.mp4
10.8 MB
Part 18-Module 02-Lesson 01_Gathering Data/06. Flat File Structure-bLKVRIhrZUY.mp4
10.8 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/15. Roll 1 Die-oJXYNArEk8k.mp4
10.8 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax-7XyFjPDPoZQ.mp4
10.8 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/16. Roll 2 Dice-OVeEr0CSe8U.mp4
10.8 MB
Part 11-Module 01-Lesson 13_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.mp4
10.8 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/26. Use Measures of Center to Compare-KFK1L4hUW80.mp4
10.8 MB
Part 04-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.mp4
10.8 MB
Part 16-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.mp4
10.8 MB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-c-v-Xa_R4SA.mp4
10.8 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/16. Binomial Distribution Conclusion-9gjCYs8f_PU.mp4
10.7 MB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/05. A Faster Algorithm-J7S3CHFBZJA.mp4
10.7 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/25. Correlation Does Not Imply Causation-aeEhfjPFiCw.mp4
10.7 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/09. Metric Choice-BeIy4A6YKrY.mp4
10.7 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/29. Formula for Location of Median-h3zyZHNyreM.mp4
10.7 MB
Part 11-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-oZkDSuhBEkE.mp4
10.7 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. Assignment Operators-p_qfzL-x3Cs.mp4
10.6 MB
Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-YPPQy_eB2mU.mp4
10.6 MB
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.mp4
10.6 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/04. Meet the Careers Team-cuKecPpZ7PM.mp4
10.6 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/20. SD of Standardized Distribution-LuI1poHmFOw.mp4
10.6 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ivBGyL3SzO0.mp4
10.6 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/08. Overview of Business Example-tlSe7H9BDy8.mp4
10.6 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/32. Enter Update Exit-0SU3cKsWsPw.mp4
10.6 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/01. Introduction to Multiple Linear Regression-b26v8HK-8-o.mp4
10.6 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/13. Dummy Variables Recap-r7Lek8rsIcg.mp4
10.6 MB
Part 11-Module 01-Lesson 07_Regressions/17. Coding It Up-BTFOf2qXy5U.mp4
10.5 MB
Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-zxnijlBCSpE.mp4
10.5 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/04. Picking the Most Suitable Metric-GAfPvj2SSiE.mp4
10.5 MB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.mp4
10.5 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/01. Introduction-QXxtu_gdWQs.mp4
10.4 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/02. Introduction-QXxtu_gdWQs.mp4
10.4 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/25. Using Sampling Distribution-NUY4Qobhojg.mp4
10.4 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/23. Keeping Trust and Drawing Circles-pBLeU5bbKak.mp4
10.4 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps-zSSNWZuVG8Y.mp4
10.4 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-zovzbp_Rpu4.mp4
10.4 MB
Part 13-Module 01-Lesson 04_Design Principles/36. Less is More-urgyRvfWPtU.mp4
10.4 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/16. Pandas groupby()-smBMJlpWdVI.mp4
10.4 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/16. Pandas groupby()-smBMJlpWdVI.mp4
10.4 MB
Part 11-Module 01-Lesson 16_Tying It All Together/01. Introduction-8tm1144C4T0.mp4
10.4 MB
Part 18-Module 02-Lesson 01_Gathering Data/03. Finding the Best Movies-aq3qM2EkwrI.mp4
10.4 MB
Part 13-Module 01-Lesson 07_Narrative Structures/27. Defining a Join-Xo-OJXzS0tQ.mp4
10.4 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.mp4
10.4 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.mp4
10.4 MB
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.mp4
10.4 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/09. Handling Attributes-YSEGZMBbxTk.mp4
10.4 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/13. Mu-GXY-iMfZTn0.mp4
10.3 MB
Part 13-Module 01-Lesson 04_Design Principles/51. D3 Functions-4OkB_Ybo0i0.mp4
10.3 MB
Part 03-Module 01-Lesson 20_L8 Estimation/23. CI Bounds-T9VX2KvzJ-k.mp4
10.3 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-Q2M8xyY47fc.mp4
10.3 MB
Part 09-Module 01-Lesson 03_Explore One Variable/09. Be Skeptical Outliers and Anomalies-kAisC2wRGBU.mp4
10.3 MB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/05. What Motivates You at the Workplace-Aa9SFwiRbho.mp4
10.3 MB
Part 03-Module 01-Lesson 20_L8 Estimation/27. Results from Sample-ypIyvJyZAs8.mp4
10.3 MB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/07. Format-Xlqoq-SoJso.mp4
10.3 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/05. DF - Add to 10-mb1eR8nb9t4.mp4
10.3 MB
Part 09-Module 01-Lesson 01_What is EDA/05. Goals of EDA-NEvuulahg2g.mp4
10.3 MB
Part 19-Module 01-Lesson 02_Design/08. Data Ink Ratio-gW2FapuYV4A.mp4
10.3 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge-DMhldSg2_vs.mp4
10.2 MB
Part 11-Module 01-Lesson 14_Validation/15. Validation Mini-Project Video-dlbeMlRoFd4.mp4
10.2 MB
Part 17-Module 01-Lesson 16_Logistic Regression/02. Fitting Logistic Regression-Dg0rBDQnIYg.mp4
10.2 MB
Part 03-Module 01-Lesson 20_L8 Estimation/05. Approximate Margin of Error-P4gLGxQrKjY.mp4
10.2 MB
Part 05-Module 02-Lesson 01_Data and Tables/13. Uniqueness and Keys-TIayTr4y9RA.mp4
10.2 MB
Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores-2OKqKX7DnMQ.mp4
10.2 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/13. Getting Data into MongoDB-hi6g1NE3sPk.mp4
10.2 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-BHFxJmzw1gY.mp4
10.2 MB
Part 17-Module 01-Lesson 16_Logistic Regression/04. Fitting Logistic Regression In Python-baQf-XiZQQ4.mp4
10.2 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/16. Pandas Series apply()-c8SD8zn5FTo.mp4
10.2 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/17. Pandas Series apply()-c8SD8zn5FTo.mp4
10.2 MB
Part 13-Module 01-Lesson 07_Narrative Structures/15. One Human Heartbeat-unKu-dmor2w.mp4
10.2 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/33. Probability of Obtaining Mean--boAkUs-amM.mp4
10.2 MB
Part 11-Module 01-Lesson 02_Naive Bayes/07. Intro To Stanley Terrain Classification-TwFhCeov85E.mp4
10.1 MB
Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.mp4
10.1 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/08. t-Table-lccjSiVTx7c.mp4
10.1 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-_Lp_3KUltFk.mp4
10.1 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-KrZpJwPlSbA.mp4
10.1 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/32. Keyboards-0m5k7Ni1O48.mp4
10.1 MB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/01. Intro-vek87HVWexE.mp4
10.1 MB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/01. Intro-vek87HVWexE.mp4
10.1 MB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.mp4
10.1 MB
Part 07-Module 01-Lesson 01_GitHub Review/01. Introduction-Vnj2VNQROtI.mp4
10.1 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-Zdl01HMSjTw.mp4
10.0 MB
Part 13-Module 01-Lesson 05_Dimple.js/01. Dimple Interlude-bo8_lJucTPI.mp4
10.0 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/12. Plot Colors for Qualitative Factors-2ZVGl6LrOPw.mp4
10.0 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/18. Debugging Data Analysis Code -l1pZZKsESAc.mp4
10.0 MB
Part 13-Module 01-Lesson 05_Dimple.js/09. Inspecting Variables and Data-eA8i6-n-Vc4.mp4
10.0 MB
Part 13-Module 01-Lesson 07_Narrative Structures/02. Approaches to Journalism-AxFSDfKP7Zs.mp4
10.0 MB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/04. Describe Your Work Experiences-B1LED4txinI.mp4
9.9 MB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/04. Describe Your Work Experiences-B1LED4txinI.mp4
9.9 MB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences-B1LED4txinI.mp4
9.9 MB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/21. 37. Insomnia-HbnB5SQqmoM.mp4
9.9 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/01. Introduction to Course-gR_buSP6sdw.mp4
9.9 MB
Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.mp4
9.9 MB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-XDvus8zHJbA.mp4
9.9 MB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components-DVvLiKedRw4.mp4
9.9 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/05. Critical Values 0.001-AdLGLYYYVao.mp4
9.9 MB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/01. Introduction to Data Visualization-MUZXLvBI2sw.mp4
9.9 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/01. Introduction to Data Visualization-MUZXLvBI2sw.mp4
9.9 MB
Part 12-Module 01-Lesson 05_Interview Practice/02. Describe your latest data project-wkWDrSBBtz0.mp4
9.9 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-MLGu66F25qU.mp4
9.9 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-MLGu66F25qU.mp4
9.9 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/16. Type Type Conversion-yN6Fam_vZrU.mp4
9.9 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel-j5tA__Dq-sQ.mp4
9.9 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/11. How Do I Find Time for My Nanodegree Program-d-VfUw7wNEQ.mp4
9.8 MB
Part 03-Module 01-Lesson 11_L4 Variability/13. Match Boxplots-imNv6Q8GiQM.mp4
9.8 MB
Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1-bFDJ_FstSZ4.mp4
9.8 MB
Part 11-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video-sJzKx_FiMXA.mp4
9.8 MB
Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-OGK9SHt8SWg.mp4
9.8 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-FC_GNjqj5zI.mp4
9.8 MB
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.mp4
9.7 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.mp4
9.7 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/01. Introduction to Aggregations-5vRf_Ntoxfw.mp4
9.7 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/04. Test Cases-7CNatJ7PqZ4.mp4
9.7 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/03. Two-Dimensional NumPy Arrays-UFcCmB7Xvvs.mp4
9.6 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/03. Two-Dimensional NumPy Arrays-UFcCmB7Xvvs.mp4
9.6 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/22. Find P-Value-pwQ7IQgremk.mp4
9.6 MB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/10. 27. English Teaching-HmsNljRIsr4.mp4
9.6 MB
Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-lWjaCJazJE0.mp4
9.6 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/13. Karma-cNFMJpVQlKY.mp4
9.6 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/12. Which Distribution-tTb1k27rhgI.mp4
9.6 MB
Part 05-Module 01-Lesson 05_Data Quality/09. Auditing Validity-B9vjn8IYaSg.mp4
9.6 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-tfhsgVCX2Ao.mp4
9.6 MB
Part 15-Module 01-Lesson 02_Design Principles/01. Introduction-Q0lZkNF6O0g.mp4
9.6 MB
Part 19-Module 01-Lesson 02_Design/01. Introduction-Q0lZkNF6O0g.mp4
9.6 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/15. Sets and groups with Trina-I59eqlvfMZk.mp4
9.5 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/10. Two-Tailed Critical Values 0.05-VCdJJTk2Izk.mp4
9.5 MB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/09. Matrix Transposes-NVK5xCY3CZE.mp4
9.5 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/30. Hot Beverage-r-TWqzDJZJs.mp4
9.5 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/26. Confidence Interval Case Breakdown-gycmvQqw-8s.mp4
9.5 MB
Part 13-Module 01-Lesson 07_Narrative Structures/03. Correlation vs Causation-8u96-UEf_ms.mp4
9.5 MB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/16. 34. Landmines-8ScnVyC24s8.mp4
9.5 MB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.mp4
9.5 MB
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.mp4
9.5 MB
Part 21-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.mp4
9.5 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/03. Unit of Diversion Example-_-BxFJTBNMM.mp4
9.4 MB
Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI-llyWJTM8V5o.mp4
9.4 MB
Part 13-Module 01-Lesson 07_Narrative Structures/30. Thinking with Venn Diagrams-C1aHeMSeIdk.mp4
9.4 MB
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.mp4
9.4 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/12. Final Tips-1ZVBvM54hQw.mp4
9.4 MB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.mp4
9.4 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/18. Joining Subqueries-rxy-fE5GeLY.mp4
9.4 MB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.mp4
9.4 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/10. Two-Tailed t-Test-zlHtHBeJhww.mp4
9.3 MB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/08. Notation Intro-xHwIU4j3gBc.mp4
9.3 MB
Part 03-Module 01-Lesson 11_L4 Variability/40. Jelly Beans-1HmiArFN-EI.mp4
9.3 MB
Part 13-Module 01-Lesson 05_Dimple.js/30. EDA vs Sketching Data Visualizations-hFlVFyatBF0.mp4
9.3 MB
Part 12-Module 01-Lesson 01_Ace Your Interview/01. Introduction-pg4HUMgKLxI.mp4
9.3 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-j0qfuunqym8.mp4
9.3 MB
Part 21-Module 01-Lesson 04_Functions/01. Introduction-p5L4rTV1Pgk.mp4
9.3 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/50. Goodbye and Keep Learning-B4EKdtRmv60.mp4
9.2 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/19. Plotting for DataFrames-CDVgPA0Mv2o.mp4
9.2 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/19. Plotting for DataFrames-CDVgPA0Mv2o.mp4
9.2 MB
Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds-Bs-wLbPOAfs.mp4
9.2 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/03. The Benefits of Interactivity-fIIyFYQyGLk.mp4
9.2 MB
Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-joTa_FeMZ2s.mp4
9.2 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-tGHQsk1SGGU.mp4
9.2 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/06. r^2-X5F1reyQ_5U.mp4
9.2 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/19. Lessons Completed in First Week -nZq-Y2lfjpY.mp4
9.2 MB
Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-TIgfjmp-4BA.mp4
9.1 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (After Cleaning)-OF2486euiRE.mp4
9.1 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data-zQj_waidR5w.mp4
9.1 MB
Part 05-Module 01-Lesson 05_Data Quality/13. Auditing Accuracy-mADDYP7ldl4.mp4
9.1 MB
Part 18-Module 03-Lesson 01_Assessing Data/07. Visual Assessment -GVVibuIg3Ro.mp4
9.1 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/28. Conclusion-rrSNkPGJmTc.mp4
9.1 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.mp4
9.1 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/21. Size vs. Power Trade-Off-bnTIVGBkKhM.mp4
9.1 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/18. Averaging Locations-GLQJukg-0fQ.mp4
9.1 MB
Part 13-Module 01-Lesson 04_Design Principles/35. Chartjunk-jm2qOX2Q2HQ.mp4
9.1 MB
Part 15-Module 01-Lesson 02_Design Principles/16. Gráfico Lixo-jm2qOX2Q2HQ.mp4
9.1 MB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/04. Algorithm Options-S-cGZ-FEdjQ.mp4
9.1 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/33. What Happened-LOwWWIXvnhU.mp4
9.0 MB
Part 03-Module 01-Lesson 20_L8 Estimation/19. Engagement Ratio-vpwCy5Gphrw.mp4
9.0 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/10. -v5CqqhgvG-U.mp4
9.0 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/23. Connecting Errors and P-Values-hFNjd5l9CLs.mp4
9.0 MB
Part 18-Module 02-Lesson 01_Gathering Data/09. Trees-OVeJU18ADmw.mp4
9.0 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.mp4
9.0 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.mp4
9.0 MB
Part 11-Module 01-Lesson 11_Text Learning/14. Why Upweight Rare Words-xYQb6f1SIEk.mp4
9.0 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/13. Explanatory vs Exploratory-SHq_zbB4ITo.mp4
9.0 MB
Part 19-Module 01-Lesson 02_Design/13. Using Color-6bAedqD3ilw.mp4
8.9 MB
Part 03-Module 01-Lesson 11_L4 Variability/32. SD Social Networkers-R6KT9-ZbQ4c.mp4
8.9 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.mp4
8.8 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.mp4
8.8 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/34. Completing the Update Function-lUYD6lldDeU.mp4
8.8 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/08. Document Selectors And Queries-xQbKGc-Ptao.mp4
8.8 MB
Part 13-Module 01-Lesson 04_Design Principles/38. Data Ink Ratio-CJouyPxHb84.mp4
8.8 MB
Part 15-Module 01-Lesson 02_Design Principles/17. Data Ink Ratio-CJouyPxHb84.mp4
8.8 MB
Part 21-Module 01-Lesson 01_Why Python Programming/04. L1 02 Course Overview V4-vFxXSIV5cHM.mp4
8.8 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts-zbjRiYSSR_Y.mp4
8.8 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/20. Interactions And Higher Order Terms-AOfXMiJgo48.mp4
8.7 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-wqvEtUA0n-s.mp4
8.7 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys-mFPq74OMkKk.mp4
8.7 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-zxeKDuSK31M.mp4
8.7 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/35. Visualization and D3 Basics-ueKb1OghNEU.mp4
8.7 MB
Part 13-Module 01-Lesson 04_Design Principles/25. Communicating with Color-QnFtYKXf7TQ.mp4
8.7 MB
Part 15-Module 01-Lesson 02_Design Principles/13. Communicating with Color-QnFtYKXf7TQ.mp4
8.7 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/22. Variability Example-kTXI_wnTbVk.mp4
8.7 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.mp4
8.7 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.mp4
8.7 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-WnQoZzxas-g.mp4
8.7 MB
Part 18-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment -BNRJdhA8_s8.mp4
8.7 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/08. Statistical vs. Practical Differences-RKHD1wzxxPA.mp4
8.7 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/03. Developer Tools and Console-C2Ob9vkpQ7g.mp4
8.6 MB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/02. Purpose-7F7cMCTcyhM.mp4
8.6 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/04. NumPy Arrays-UG924zKZF7U.mp4
8.6 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/05. NumPy Arrays-UG924zKZF7U.mp4
8.6 MB
Part 09-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation-Mak839YmmrA.mp4
8.6 MB
Part 19-Module 01-Lesson 02_Design/03. Exploratory vs. Explanatory Analysis-wvgBSMks4p8.mp4
8.6 MB
Part 12-Module 02-Lesson 04_Maps and Hashing/01. Introduction to Maps-JEw3iQAnGKQ.mp4
8.6 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/05. Introduction to D3-mP1P0ybdZqI.mp4
8.6 MB
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.mp4
8.6 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/20. Building the Linear Model-zyIc0sXYk2A.mp4
8.6 MB
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.mp4
8.6 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-T5TBKcjzleI.mp4
8.6 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/03. Confirming Inputs-8lPTOG1yLsg.mp4
8.6 MB
Part 05-Module 01-Lesson 05_Data Quality/19. More About Correcting Data-vWBMgSQvsVk.mp4
8.6 MB
Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-StmEUgT1XSY.mp4
8.5 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.mp4
8.5 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.mp4
8.5 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. Assess Intro -vj3CYBlWj3k.mp4
8.5 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/32. Keyboards-bLDBg86nm6o.mp4
8.5 MB
Part 13-Module 01-Lesson 04_Design Principles/54. The Spectrum of Tech in Data Vis-4-tLvLvX9U4.mp4
8.5 MB
Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet -K-Owid_mf8o.mp4
8.5 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/15. Experiment Design and Sizing Overview-6_odiPIKZO0.mp4
8.4 MB
Part 18-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 Solution-E5tAoCK6GcQ.mp4
8.4 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/14. What is the Question-xQJyObqxg3E.mp4
8.4 MB
Part 11-Module 01-Lesson 03_SVM/10. SVM in SKlearn-R7xQtQzkvTk.mp4
8.4 MB
Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio-XtDLvgt7LQk.mp4
8.4 MB
Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.mp4
8.4 MB
Part 21-Module 01-Lesson 04_Functions/11. L4 08 Lambda Expressions V3-wkEmPz1peJM.mp4
8.4 MB
Part 11-Module 01-Lesson 07_Regressions/20. Extracting Score Data from sklearn-NhD4oUuhvO8.mp4
8.3 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/08. Efficiency of Bubble Sort-KddkHygi7is.mp4
8.3 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-nsG26Dz9z44.mp4
8.3 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/01. Introduction-aAmMK8tGEYc.mp4
8.3 MB
Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.mp4
8.3 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05-TyqZdKR8J_w.mp4
8.3 MB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites-0ANDJ8i_deE.mp4
8.3 MB
Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-1Hd1Bq1YxXg.mp4
8.3 MB
Part 13-Module 01-Lesson 05_Dimple.js/20. Object Oriented Design and Charts-2uzNpGWdavc.mp4
8.3 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/07. Bubble Sort-h_osLG3GmjE.mp4
8.3 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/10. Traditional Confidence Interval Methods-DmZwYHuz2eM.mp4
8.3 MB
Part 13-Module 01-Lesson 04_Design Principles/31. Red Green Color Blindness-iqbqj9kbapM.mp4
8.2 MB
Part 11-Module 01-Lesson 13_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.mp4
8.2 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/08. Extracting Data-OeiBJ_D-ZsM.mp4
8.2 MB
Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-CvTXyvw7QLc.mp4
8.2 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/09. What We Need to Compare the Means-y27MBpbnP48.mp4
8.2 MB
Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-BRL0ZuvBm0U.mp4
8.2 MB
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-vLlj5nNj8x4.mp4
8.2 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/22. Decomposing Visualizations-iJ8t2FsPW4c.mp4
8.2 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-MlE3BuOvWnU.mp4
8.2 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/10. NumPy Index Arrays-MlE3BuOvWnU.mp4
8.2 MB
Part 05-Module 02-Lesson 01_Data and Tables/10. How Queries Happen-v3EkXogyIL4.mp4
8.2 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/15. Nested Selections-y3kJorrQrJg.mp4
8.2 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/27. Klout Parameters-wV-6gQepmn0.mp4
8.2 MB
Part 12-Module 01-Lesson 03_Interview Fails/01. Interview Fails-FD6UNqMa0xc.mp4
8.1 MB
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-t0iflCpBUDA.mp4
8.1 MB
Part 05-Module 01-Lesson 05_Data Quality/04. Sources of Dirty Data-h12MQ3d1Z1Y.mp4
8.1 MB
Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.mp4
8.1 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision-pZu3Gr5cAUU.mp4
8.1 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-kTsQyHV_T5E.mp4
8.1 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/21. Rankings of Visual Encodings-ycsXqX7T80Y.mp4
8.1 MB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/08. Rankings of Visual Encodings - Data Visualization and D3.js-ycsXqX7T80Y.mp4
8.1 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/19. Finches - Decision-9N6i3RZun5A.mp4
8.1 MB
Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-MEtIAGKweXU.mp4
8.1 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/03. Meal Prices-gzu9UcNF0_k.mp4
8.1 MB
Part 11-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.mp4
8.1 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/03. Get to Know the PDF-52HAbu6_u9I.mp4
8.1 MB
Part 11-Module 01-Lesson 11_Text Learning/11. Stemming with NLTK-gWbkW_cyNs8.mp4
8.1 MB
Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-DxCwtkrYR-s.mp4
8.1 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-lEl0alktZkM.mp4
8.1 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-lEl0alktZkM.mp4
8.1 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/21. Shape of Distribution When n Increases-kJ4Y8a1rOkY.mp4
8.1 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/09. Continuous Distribution-ytUY1_EfxPk.mp4
8.0 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/05. Setting Up Hypotheses - Part II-nByvHz77GiA.mp4
8.0 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-SxCK2_82FfQ.mp4
8.0 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/28. Outlining the Update Function-k5ZZQ3ulwX4.mp4
8.0 MB
Part 21-Module 01-Lesson 03_Control Flow/02. Indentation-G8qUNOTHtrM.mp4
8.0 MB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/08. Exact and Approximate Algorithms-3A8YqOYlAwQ.mp4
8.0 MB
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-S-pjRUJAGTs.mp4
8.0 MB
Part 12-Module 02-Lesson 02_List-Based Collections/08. Stacks-DQoCO8aGcNc.mp4
8.0 MB
Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.mp4
8.0 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.mp4
8.0 MB
Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-X_AS8NBngsk.mp4
8.0 MB
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-hxxa0KAkB1o.mp4
8.0 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ZhWxuf5czTA.mp4
8.0 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null-7AGEhuipHl4.mp4
8.0 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bgyN3RO2ICo.mp4
8.0 MB
Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bgyN3RO2ICo.mp4
8.0 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/02. Alpha Levels-VuEwqXDd1Rs.mp4
7.9 MB
Part 03-Module 01-Lesson 11_L4 Variability/34. Spreadsheet SD-gqXiI9v7h8A.mp4
7.9 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -oWu4UDkPmj8.mp4
7.9 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/19. Using Beautiful Soup-_rDjie-TaS8.mp4
7.9 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 2-W2tL3QSBi3k.mp4
7.9 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-LlPsmQx5y50.mp4
7.9 MB
Part 17-Module 01-Lesson 16_Logistic Regression/31. Final Thoughts On Shifting To Machine Learning-YkZFjZ3Fx8A.mp4
7.9 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-KhGfaSWoEn0.mp4
7.9 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.mp4
7.9 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/29. 11 CASE V2-BInXuTY_FzE.mp4
7.9 MB
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-HEnJRwJ23us.mp4
7.9 MB
Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts-q-EjlMl1Bj4.mp4
7.9 MB
Part 16-Module 03-Lesson 02_SQL Joins/14. Other JOINs-4edRxFmWUEw.mp4
7.9 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/06. Wide and Long Format-zlaeISxRESQ.mp4
7.9 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/44. Adding Events to Buttons-aejs122BTzA.mp4
7.9 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.mp4
7.8 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/08. Map Distortions-xL5xVEuLuNE.mp4
7.8 MB
Part 17-Module 01-Lesson 16_Logistic Regression/09. Model Diagnostics-XsYFAtzF6e4.mp4
7.8 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-5GYA5j1fqBU.mp4
7.8 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/31. Raining-R5Jgz8SaVqM.mp4
7.8 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/24. Conclusions In Hypothesis Testing-I0Mo7hcxahY.mp4
7.8 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-QCakJ5gxF5w.mp4
7.8 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/26. Where are we-d3jQdOuOy8k.mp4
7.8 MB
Part 14-Module 01-Lesson 05_Analyzing Results/01. Introduction-AyeKXinJ3W8.mp4
7.8 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/19. Null Hypothesis-Klv_8052hoA.mp4
7.8 MB
Part 09-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.mp4
7.8 MB
Part 21-Module 01-Lesson 05_Scripting/06. Programming Environment Setup-EKxDnCK0NAk.mp4
7.8 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/21. Duration vs. Exposure Example-993P7ivCrnQ.mp4
7.8 MB
Part 11-Module 01-Lesson 02_Naive Bayes/38. Naive Bayes Mini-Project Video-UH2oSijkszo.mp4
7.8 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.mp4
7.8 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-sLEF-B1fkX8.mp4
7.7 MB
Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.mp4
7.7 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/24. The Facebook Offering Animation-s7h2tH6z9Rg.mp4
7.7 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score-1xXceRXrsg8.mp4
7.7 MB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/06. Dynamic Programming-VQeFcG9pjJU.mp4
7.7 MB
Part 21-Module 01-Lesson 05_Scripting/26. Third Party Libraries And Package Managers-epOze9gC6T4.mp4
7.7 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-HVa4G8jQbEo.mp4
7.7 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-HVa4G8jQbEo.mp4
7.7 MB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/07. Matrix Multiplication Part 2-8jtk8BzBdj8.mp4
7.7 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/28. Multiple Testing Corrections-DuMgeHrkIF0.mp4
7.7 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/25. Changing Bin Size-fI_SYnWB1XA.mp4
7.7 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age-GFKRNBnFGVU.mp4
7.7 MB
Part 03-Module 01-Lesson 11_L4 Variability/29. One Dimension-vsqelq1aYy8.mp4
7.7 MB
Part 11-Module 01-Lesson 09_Clustering/02. Clustering Movies-g8PKffm8IRY.mp4
7.7 MB
Part 11-Module 01-Lesson 07_Regressions/37. Regression Mini-Project Video-CrD9jN3rBM8.mp4
7.6 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-1R44jvxIPJY.mp4
7.6 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/23. Convert to Z-Score-UAHkVUloKbg.mp4
7.6 MB
Part 12-Module 02-Lesson 05_Trees/06. Depth-First Traversals-wp5ohHFTieM.mp4
7.6 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/18. UNC-Ko-g24l1LpQ.mp4
7.6 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/19. What Is A P-value Anyway-eU6pUZjqviA.mp4
7.6 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05-oCQnqFE4uxQ.mp4
7.6 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather Intro-K5ITQn1L1R0.mp4
7.6 MB
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-HyjBus7S2gY.mp4
7.6 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.mp4
7.6 MB
Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-cwjvMYPB1Fk.mp4
7.6 MB
Part 18-Module 02-Lesson 01_Gathering Data/20. Flashforward 2-Sbyn8aT-8G8.mp4
7.6 MB
Part 09-Module 01-Lesson 02_R Basics/16. Advice for Data Scientists-FdkhUOtHIFg.mp4
7.6 MB
Part 18-Module 02-Lesson 01_Gathering Data/13. Text File Structure-O4qEWpXZLQg.mp4
7.6 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-eZ_yCrh4740.mp4
7.6 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/22. Conduct Hypothesis Test-EeI8F1_7zbQ.mp4
7.6 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/02. Probability-oR8H9vdtreE.mp4
7.6 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20-YaznAtppruA.mp4
7.6 MB
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-t2Nq3MFK_pg.mp4
7.5 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/09. Between 118 and 226-pHNtOrr6bgE.mp4
7.5 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-lVLgiRRhFpQ.mp4
7.5 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-lVLgiRRhFpQ.mp4
7.5 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-kT0jBsXOouw.mp4
7.5 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.mp4
7.5 MB
Part 18-Module 02-Lesson 01_Gathering Data/16. JSON File Structure-hO2CayzZBoA.mp4
7.5 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/26. Rent - Cohen's d-admfaazbCnY.mp4
7.5 MB
Part 04-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.mp4
7.5 MB
Part 16-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.mp4
7.5 MB
Part 03-Module 01-Lesson 11_L4 Variability/15. Problem with IQR-h5l2EP3DR-4.mp4
7.5 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/09. Querying Using Field Selection-V2UMNT9VBrw.mp4
7.5 MB
Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-djTM5fADIVs.mp4
7.4 MB
Part 03-Module 01-Lesson 11_L4 Variability/38. Bessel's Correction-bHVPpomkUYs.mp4
7.4 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-6LgGDqQLpyc.mp4
7.4 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.mp4
7.4 MB
Part 03-Module 01-Lesson 11_L4 Variability/34. Spreadsheet SD-sXeVydVAv7Q.mp4
7.4 MB
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.mp4
7.4 MB
Part 18-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces) 2-tobH58uO24U.mp4
7.4 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/01. Introduction-0ydaJl3wCkU.mp4
7.4 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-2DwKMiFjGPE.mp4
7.4 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/04. Total Number of Samples-q5JgPXsHSrA.mp4
7.4 MB
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-tjEua8efugg.mp4
7.4 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/04. Assessing the Quality of Data Pt. 2-8onBHqvvrig.mp4
7.4 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/23. Rent - t-Critical Values-0tcbCIrJGlM.mp4
7.4 MB
Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.mp4
7.4 MB
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-GuBics_6HOk.mp4
7.3 MB
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-ydpbvqLmLQI.mp4
7.3 MB
Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.mp4
7.3 MB
Part 11-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm-hGKY6BAqJ6o.mp4
7.3 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/29. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA.mp4
7.3 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/03. How This Lesson Is Structured-xfRtO4aFpv0.mp4
7.3 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/14. Increase t-tBk_gBWan8k.mp4
7.3 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median--XPrm7KcCdc.mp4
7.3 MB
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.mp4
7.3 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.mp4
7.3 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.mp4
7.3 MB
Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-YZb-Uam-Ics.mp4
7.3 MB
Part 14-Module 01-Lesson 05_Analyzing Results/03. Choosing Invariants-qCnbDgy2yHk.mp4
7.3 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/21. Querying Arrays Using Scalars-8uhfnWgiBHM.mp4
7.3 MB
Part 07-Module 01-Lesson 01_GitHub Review/08. Writing READMEs with Walter-DQEfT2Zq5_o.mp4
7.3 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/02. USCF Distribution-GNAZ2S3igr4.mp4
7.3 MB
Part 11-Module 01-Lesson 09_Clustering/11. K-Means Clustering Visualization 3-WfwX3B4d8_I.mp4
7.3 MB
Part 09-Module 01-Lesson 03_Explore One Variable/02. What to Do First-TgAIx_NFaD8.mp4
7.2 MB
Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-jfGdUdo37Vk.mp4
7.2 MB
Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-OB7iJnEY0Tg.mp4
7.2 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NkyYCLoJVyE.mp4
7.2 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-Mta8Hv36k7Q.mp4
7.2 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-Mta8Hv36k7Q.mp4
7.2 MB
Part 12-Module 01-Lesson 04_Land a Job Offer/01. Land a Job Offer-ZQJoT8QL_hw.mp4
7.2 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/09. The Data Science Process-Kxp2TNV3n5k.mp4
7.2 MB
Part 03-Module 01-Lesson 20_L8 Estimation/10. 95 CI with Exact Z-Scores-Ipj62kdE3Lo.mp4
7.2 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/15. Calculating a Confidence Interval-T-QWVJtXHAs.mp4
7.2 MB
Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.mp4
7.2 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/02. One Number to Describe Data-6QfvhQ0En0E.mp4
7.2 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-xPZOSx1q_dg.mp4
7.1 MB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/01. Choose Your own Algorithm-tpbHNLv-HT0.mp4
7.1 MB
Part 14-Module 01-Lesson 05_Analyzing Results/20. Course Conclusion-6aBIwp3n7_8.mp4
7.1 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/36. Hypothesis Testing-GyLWb1FBJsA.mp4
7.1 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.mp4
7.1 MB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/07. Traveling Salesman Problem-9ruR5Ux63QU.mp4
7.1 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/08. Standard Deviation Calculation-H5zA1A-XPoY.mp4
7.1 MB
Part 19-Module 01-Lesson 02_Design/16. General Design Tips-Zq-wMwOfQqY.mp4
7.1 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-k8Ru6RQJbd4.mp4
7.1 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-k8Ru6RQJbd4.mp4
7.1 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/06. Runtime Analysis-8bI9OgOB2qI.mp4
7.1 MB
Part 11-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning-Xcb9jjjAm60.mp4
7.1 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure-z_Gp9ttyiwg.mp4
7.1 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-iu6CxSkq-wg.mp4
7.1 MB
Part 13-Module 01-Lesson 04_Design Principles/24. Redundant Encodings-RU3rI_pO8Rc.mp4
7.1 MB
Part 14-Module 01-Lesson 05_Analyzing Results/06. Checking Invariants, Part 2-Mftti4FSjn4.mp4
7.0 MB
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.mp4
7.0 MB
Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-S1yjJWWza7g.mp4
7.0 MB
Part 13-Module 01-Lesson 07_Narrative Structures/01. Finding Stories-vVWFVaiWomw.mp4
7.0 MB
Part 21-Module 01-Lesson 05_Scripting/02. Python Installation-2_P05aYChqQ.mp4
7.0 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.mp4
7.0 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import-tU1N-8aNB_M.mp4
7.0 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-3pT4mwTqxoA.mp4
7.0 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/33. Highlight Countries-bq_gVndUj1U.mp4
7.0 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-iJEBxsKDDoE.mp4
7.0 MB
Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.mp4
7.0 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/22. Looking at Samples of Households-kQePh6UTB90.mp4
7.0 MB
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.mp4
7.0 MB
Part 12-Module 02-Lesson 05_Trees/10. Binary Search Trees-7-ZQrugO-Yc.mp4
7.0 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/03. Types of Effect-Size Measures-FWSS2VadyBg.mp4
6.9 MB
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.mp4
6.9 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/28. Variability Summary-sDejdrYe8cg.mp4
6.9 MB
Part 05-Module 02-Lesson 01_Data and Tables/15. Joining Tables-lXoiI0gx3MU.mp4
6.9 MB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/02. What's Ahead-ggbCydfI1JM.mp4
6.9 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-8_SBvU8NYak.mp4
6.9 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-8_SBvU8NYak.mp4
6.9 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.mp4
6.9 MB
Part 05-Module 01-Lesson 05_Data Quality/02. What is Data Cleaning-dzqOwmxK3j4.mp4
6.9 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1-J4X9r0EGH3k.mp4
6.9 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/02. Lesson Overview-1EzlGH4Biu0.mp4
6.9 MB
Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-5571wc0iWCI.mp4
6.9 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-KYAUEz-50-Q.mp4
6.9 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-KYAUEz-50-Q.mp4
6.9 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2-ZXy8jgywY5g.mp4
6.9 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-veRRrAR2xF4.mp4
6.9 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-veRRrAR2xF4.mp4
6.9 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/24. all Operator-B3iYl-2HSXI.mp4
6.9 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/15. Why Even Create Graphics-lqI3LFwMVUc.mp4
6.9 MB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Why Even Create Graphics - Data Visualization and D3.js-lqI3LFwMVUc.mp4
6.9 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/08. Hierarchies with Trina-ys8Cn0o5gNI.mp4
6.9 MB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/03. Hierarchies with Trina-ys8Cn0o5gNI.mp4
6.9 MB
Part 17-Module 01-Lesson 06_Conditional Probability/01. Introduction to Conditional Probability-Ok8948Wcbmo.mp4
6.9 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Why the Standard Deviation-XlTBvjQ2t8w.mp4
6.9 MB
Part 03-Module 01-Lesson 11_L4 Variability/30. Standard Deviation-0seYYIPBXxI.mp4
6.8 MB
Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-XqEQG4qo94I.mp4
6.8 MB
Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.mp4
6.8 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center-bsybN1HIH4s.mp4
6.8 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-UNqgFhKvCL4.mp4
6.8 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/32. Location of Mean on Distribution-_kADa-a_UD8.mp4
6.8 MB
Part 11-Module 01-Lesson 02_Naive Bayes/04. Features and Labels Musical Example-rnv0-lG9yKU.mp4
6.8 MB
Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-VYwgHHqaUII.mp4
6.8 MB
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-9JHRpVTMuK4.mp4
6.8 MB
Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts-i6nppkOcNoE.mp4
6.8 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-S4KbzIyEwV8.mp4
6.8 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/03. Normalized Design Part Two-l6SDnhM7B_k.mp4
6.8 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/12. Drawing and Altering the Map-soflPyVhb6o.mp4
6.8 MB
Part 03-Module 01-Lesson 11_L4 Variability/16. Measure Variability-j5fGEYLUOD4.mp4
6.8 MB
Part 19-Module 01-Lesson 02_Design/09. Design Integrity-y72_fVFtqlY.mp4
6.8 MB
Part 12-Module 02-Lesson 05_Trees/01. Trees-PXie7f22v2Q.mp4
6.8 MB
Part 12-Module 02-Lesson 02_List-Based Collections/03. Arrays-OnPP5xDmFv0.mp4
6.8 MB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.mp4
6.8 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/06. CSVs in Python-22sQCo6ovH0.mp4
6.8 MB
Part 05-Module 01-Lesson 05_Data Quality/01. Introduction-JA7oIPaf9PM.mp4
6.8 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-T_LpzJl-EVE.mp4
6.7 MB
Part 13-Module 01-Lesson 07_Narrative Structures/65. Lesson 3 Recap-MmJ6fBojjiA.mp4
6.7 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/08. Declaring Relationships-1FjqstT1faI.mp4
6.7 MB
Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-YaZu4waSryo.mp4
6.7 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/02. Course Format-rVmwPGFtk_Y.mp4
6.7 MB
Part 13-Module 01-Lesson 07_Narrative Structures/35. Returns in the Data Binding Process-OwyrjSRb2xo.mp4
6.7 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-3kH4ei9l4h8.mp4
6.7 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/37. Probability of Mean-RNgSdHPE4aA.mp4
6.7 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/07. Fixing Data Types-7NSYtdVrlRE.mp4
6.7 MB
Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-hUmXWHOPxpI.mp4
6.7 MB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/05. Investigation Process-5o2x4UsumLY.mp4
6.7 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Notation Parameters vs. Statistics-webref_dLrA.mp4
6.6 MB
Part 13-Module 01-Lesson 05_Dimple.js/35. What's Next-mKJkmv7h9ro.mp4
6.6 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/34. From Source Code to Graphic-PIqgFTee-lk.mp4
6.6 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-TSw2AAaKxBA.mp4
6.6 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/02. AB Testing-EcWvhbIjT9o.mp4
6.6 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/19. Pooled Standard Error-iub8yWiO84I.mp4
6.6 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-32WHsQi1UWc.mp4
6.6 MB
Part 11-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.mp4
6.6 MB
Part 09-Module 01-Lesson 02_R Basics/10. Read and Subset Data-UdniaeLsViQ.mp4
6.6 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/12. Other Language Associated With Confidence Intervals-9KYVRx7-llg.mp4
6.6 MB
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8xFV-I4VqZ0.mp4
6.6 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/22. NEW D3 Scale Syntax-nqi4oT2aeAw.mp4
6.6 MB
Part 12-Module 02-Lesson 06_Graphs/06. Graph Representations-uw9u6dtl0WA.mp4
6.6 MB
Part 17-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.mp4
6.6 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/05. Cohen's d-5rXOy1S5bVk.mp4
6.6 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.mp4
6.6 MB
Part 12-Module 02-Lesson 06_Graphs/01. Graph Introduction-DFR8F2Q9lgo.mp4
6.6 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/24. Drawing Circles-GlIXt29deCA.mp4
6.6 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/21. Conclusion-JUI9VHvwI08.mp4
6.5 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/21. Conclusion-JUI9VHvwI08.mp4
6.5 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.mp4
6.5 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.mp4
6.5 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score-iHnjTqGPbVg.mp4
6.5 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.mp4
6.5 MB
Part 13-Module 01-Lesson 05_Dimple.js/31. Customizing a Dimple Chart-93MgOnKP5m0.mp4
6.5 MB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/03. Introduction Pt. III-0ZuxGhiqo5U.mp4
6.5 MB
Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-SwbreslrpqQ.mp4
6.5 MB
Part 13-Module 01-Lesson 05_Dimple.js/16. Debugging and Inspecting Chart Objects-XYMtkn0DyIM.mp4
6.5 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-R5EsIDJ0apw.mp4
6.5 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/18. Hypotheses-FDcgsIOTv94.mp4
6.5 MB
Part 09-Module 01-Lesson 01_What is EDA/09. Course Overview-W8N0aSMPff8.mp4
6.5 MB
Part 13-Module 01-Lesson 04_Design Principles/01. Lesson Overview-k5T30IHD8T8.mp4
6.5 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-uoHzcmf4yXU.mp4
6.5 MB
Part 11-Module 01-Lesson 07_Regressions/34. Comparing Classification and Regression-G_0W912qmGc.mp4
6.5 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-uSXJtEpwEVM.mp4
6.5 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/27. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.mp4
6.5 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.mp4
6.5 MB
Part 19-Module 01-Lesson 02_Design/05. What Makes a Bad Visual-zbvB_9f7bFs.mp4
6.4 MB
Part 05-Module 01-Lesson 05_Data Quality/06. Difficulty of Quality Metrics-uqCSn9Q9ARk.mp4
6.4 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/01. Intro-jOhaqX_9oy8.mp4
6.4 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/13. Quick Sort-kUon6854joI.mp4
6.4 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/29. Data Analysis and Related Terms-9g9_tlhbNSw.mp4
6.4 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/36. Groups And Sets-Yb-91NVNgTA.mp4
6.4 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-VdVjOC6UP6c.mp4
6.4 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/01. Intro-8y2JZ2gEl1k.mp4
6.4 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/01. Effect Size-z98xODInLCQ.mp4
6.4 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/07. Confidence Intervals Applications-C0wgmeRx9yE.mp4
6.4 MB
Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI-fFY4isvV-Sk.mp4
6.4 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/22. L2 08 Lists And Membership Operators V2-JAbZdZg5_x8.mp4
6.4 MB
Part 19-Module 01-Lesson 02_Design/18. Tell A Story-_IdOUEhjVGI.mp4
6.3 MB
Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-qHk-FRWnYAo.mp4
6.3 MB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/01. Case Study Introduction-r8uEDyBylHY.mp4
6.3 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/22. Comparing the Two Student Groups-6UYEM0XUSGQ.mp4
6.3 MB
Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-0L3Obq4FSVQ.mp4
6.3 MB
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-VBs6D4ggnYY.mp4
6.3 MB
Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-8ZvLpWDITn4.mp4
6.3 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.mp4
6.3 MB
Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-dkLEMSLTxvk.mp4
6.3 MB
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-_7Vqou7k7fI.mp4
6.3 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/14. Efficiency of Quick Sort-aMb5GHPGQ1U.mp4
6.3 MB
Part 12-Module 02-Lesson 06_Graphs/02. What Is a Graph-p-_DFOyEMV8.mp4
6.3 MB
Part 12-Module 02-Lesson 06_Graphs/09. Graph Traversal-Dkt-XxHZaZE.mp4
6.3 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution-QjhQztBNz-Q.mp4
6.3 MB
Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.mp4
6.3 MB
Part 09-Module 01-Lesson 01_What is EDA/02. Go Exploring-dias-YUpewk.mp4
6.3 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/01. Animation and Interaction-4aBXHspd7WI.mp4
6.3 MB
Part 19-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings-98aog0eVcC4.mp4
6.3 MB
Part 03-Module 01-Lesson 11_L4 Variability/21. Be Happy and Get Rid of Negatives-_ULZYGI6LPQ.mp4
6.2 MB
Part 11-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit-VkUpuABChT4.mp4
6.2 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/15. Roll 1 Die-NHnIYEKcnUc.mp4
6.2 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-kWsDkFkEjNM.mp4
6.2 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/29. L2 03 Sets V2-eIHNFgTFfnA.mp4
6.2 MB
Part 03-Module 01-Lesson 20_L8 Estimation/11. Generalize Point Estimate-i4lFgFq8Kpo.mp4
6.2 MB
Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Part II-1GRv1S6K8gQ.mp4
6.2 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-UMWsyRYnfPk.mp4
6.2 MB
Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means-AocpFl2wt6k.mp4
6.2 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/21. Best Practices for Scraping-97FYi0SQFQ8.mp4
6.2 MB
Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD-1SL8FGhaKqA.mp4
6.2 MB
Part 19-Module 01-Lesson 02_Design/15. Shape, Size, and other Tools-fzEliHW3ZLM.mp4
6.2 MB
Part 21-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.mp4
6.2 MB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/06. Matrix Multiplication Part 1-JRoCFQRP4B0.mp4
6.2 MB
Part 06-Module 01-Lesson 03_Analyzing Data/01. Introduction to Lesson 5-l2Nab0LY_cI.mp4
6.2 MB
Part 16-Module 03-Lesson 02_SQL Joins/18. JOINs and Filtering-aI1kbDDNs4w.mp4
6.2 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-6CiZB0N7y64.mp4
6.2 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-6CiZB0N7y64.mp4
6.2 MB
Part 16-Module 03-Lesson 01_Basic SQL/01. Introduction-Z8WNfx9Oq9s.mp4
6.2 MB
Part 03-Module 01-Lesson 20_L8 Estimation/09. Sampling Distribution-XUA8rsit0J4.mp4
6.1 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value-tef9eqI2SVY.mp4
6.1 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-cgWAzXtglF0.mp4
6.1 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs-KAOIExZuV_M.mp4
6.1 MB
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.mp4
6.1 MB
Part 09-Module 01-Lesson 01_What is EDA/07. Our Approach for This Course-dBsf-szQ00s.mp4
6.1 MB
Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.mp4
6.1 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-kutWDS1chik.mp4
6.1 MB
Part 11-Module 01-Lesson 12_Feature Selection/02. A New Enron Feature-m2-LkgEfLO0.mp4
6.1 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/19. Randomness-KwmQDhUkLAE.mp4
6.1 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/19. Randomness-KwmQDhUkLAE.mp4
6.1 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/img/party.gif
6.1 MB
Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-JKZF4qHztv0.mp4
6.1 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/13. Two-Tailed Critical Values 0.01-Fzich-V7ZO0.mp4
6.1 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic-wDjjmYJ9Z5Y.mp4
6.1 MB
Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3--XfG5hXveiE.mp4
6.1 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/15. What About More Than Two Variables -ufKcdUbLj9c.mp4
6.1 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.mp4
6.1 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.mp4
6.1 MB
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-ICUYxC-8d7o.mp4
6.0 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.mp4
6.0 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.mp4
6.0 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/40. Notation for Difference-r1X81SXRLKI.mp4
6.0 MB
Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-gg7SAMMl4kM.mp4
6.0 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-Och80L_uNjU.mp4
6.0 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=-rQivl4aJCOI.mp4
6.0 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=-rQivl4aJCOI.mp4
6.0 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/20. Outliers-HKIsvkZUZfo.mp4
6.0 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/16. Operators-PlJ_dfdEbR0.mp4
6.0 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/31. Data Join with a Key Function-ue_TULswM1Y.mp4
6.0 MB
Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-IMWsjjIeOrY.mp4
6.0 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/13. GROUP BY-9vb67TF4WV0.mp4
6.0 MB
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.mp4
6.0 MB
Part 11-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.mp4
6.0 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/03. Degrees of Freedom-ZXkeT8mN4lg.mp4
6.0 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/25. Conclusion-YS4bR1vQ3Ls.mp4
6.0 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/17. -zDs_pN7G-wQ.mp4
6.0 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/16. Indulge Curiosity-9HnRVGjqNqE.mp4
5.9 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/22. L2 09 Lists And Membership Operators V2-rNV_E50wcWM.mp4
5.9 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-n0lluEhKUfQ.mp4
5.9 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/20. Notation for Random Variables-8NxTW1u4s-Y.mp4
5.9 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/20. Clean Define-qHB4jsqcfi4.mp4
5.9 MB
Part 03-Module 01-Lesson 11_L4 Variability/12. Define Outlier-jxatUS0YvtU.mp4
5.9 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/12. Iterating on Visualizations-muh0thR2DKo.mp4
5.9 MB
Part 21-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.mp4
5.9 MB
Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-fRNDqy-le8U.mp4
5.9 MB
Part 11-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.mp4
5.9 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/20. Plotting With Pandas-kR7KZFqciFE.mp4
5.9 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean--IGW7WH6CIA.mp4
5.9 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/21. Standard Normal Distribution-5B-vrhyedws.mp4
5.9 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NTyY1HlXhiQ.mp4
5.9 MB
Part 16-Module 03-Lesson 01_Basic SQL/15. LIMIT Statement-cCPHNNhBgpQ.mp4
5.9 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/12. Ratio of SDs-L4Jgcf9FNKA.mp4
5.9 MB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/03. Dijkstra's Algorithm-SoPMK03cOgk.mp4
5.9 MB
Part 12-Module 02-Lesson 02_List-Based Collections/06. Linked Lists in Depth-ZONGA5wmREI.mp4
5.9 MB
Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-97v0kEWjcmg.mp4
5.9 MB
Part 21-Module 01-Lesson 05_Scripting/27. Experimenting With An Interpreter-hspPtnQwMPg.mp4
5.9 MB
Part 18-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment Solution-H50mPHHp6fY.mp4
5.9 MB
Part 03-Module 01-Lesson 11_L4 Variability/13. Match Boxplots-xg4WOp3v-CM.mp4
5.8 MB
Part 13-Module 01-Lesson 04_Design Principles/07. Small Multiples-HS_dsOQfwz8.mp4
5.8 MB
Part 13-Module 01-Lesson 07_Narrative Structures/24. Annotations World Cup Attendance Chart-Aq39o9xrW5A.mp4
5.8 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/16. Establishing Statistical Significance-C22VZ_mY5RM.mp4
5.8 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/12. Data-d7aERRVkccY.mp4
5.8 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/12. Data-d7aERRVkccY.mp4
5.8 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-TBJY7UsKtYU.mp4
5.8 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-P6ZOr7JiMLk.mp4
5.8 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-a2GCyz_N0oY.mp4
5.8 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/07. Sampling Distribution-7tlVeUW2t7Q.mp4
5.8 MB
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.mp4
5.8 MB
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-0QiU3p8POHk.mp4
5.8 MB
Part 03-Module 01-Lesson 11_L4 Variability/20. Equation for Average Deviation-dYbYjtCzQPo.mp4
5.8 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/15. Standardizing Each Column Again-WmJKPUthUPw.mp4
5.8 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/15. Standardizing Each Column Again-WmJKPUthUPw.mp4
5.8 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/24. Final Thoughts-CNGDocH1k3k.mp4
5.8 MB
Part 11-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.mp4
5.8 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.mp4
5.8 MB
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.mp4
5.8 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/04. Iterative Process-m2qDeWrGIDI.mp4
5.7 MB
Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-7LGaeYfvRug.mp4
5.7 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/20. Shoes - 95 CI-hN3Js3thgdY.mp4
5.7 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/01. Welcome to Evaluation Metrics Lesson-IHuFWRM9f9Q.mp4
5.7 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Calculating the Mean-1nzZxmJ8xvU.mp4
5.7 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/17. -NXGcCf1KCt4.mp4
5.7 MB
Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean-DM1zSW5aoCc.mp4
5.7 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/13. Data Modeling in JSON--rnzkOofIv0.mp4
5.7 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.mp4
5.7 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.mp4
5.7 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/14. Writing Code with DB API-Zd0PAgb6vY4.mp4
5.7 MB
Part 12-Module 02-Lesson 04_Maps and Hashing/06. Collisions-BUaWIjZ_ToY.mp4
5.7 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/32. Compute CI-nCg6F5QQZsI.mp4
5.7 MB
Part 11-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video-GJviz-sIq9w.mp4
5.7 MB
Part 18-Module 04-Lesson 01_Cleaning Data/01. Introduction -rkRn1Nh-6lg.mp4
5.7 MB
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.mp4
5.7 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/14. Confidence Intervals-fDkfHKODOcQ.mp4
5.7 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Background Of Bootstrapping-6Vg5kGoDl7k.mp4
5.6 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/19. D3 Scales-pFRoUknUJl8.mp4
5.6 MB
Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-5zoL8YdM6sI.mp4
5.6 MB
Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-PZSPhQCVABg.mp4
5.6 MB
Part 17-Module 01-Lesson 14_Regression/13. Fitting A Regression Line-xQob80zrT3s.mp4
5.6 MB
Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-7HMAtB-342I.mp4
5.6 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.mp4
5.6 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.mp4
5.6 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-0plipvHyAlk.mp4
5.6 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-0plipvHyAlk.mp4
5.6 MB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.mp4
5.6 MB
Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-bR7EoKjN0EM.mp4
5.6 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/16. Assess Programmatic-6JubHCD7dh4.mp4
5.6 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/03. Degrees of Freedom-nJlJ0vlTRUs.mp4
5.6 MB
Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.mp4
5.6 MB
Part 19-Module 01-Lesson 02_Design/07. Chart Junk-3BTBEYOG2o8.mp4
5.6 MB
Part 13-Module 01-Lesson 05_Dimple.js/29. From Bars to Circles to Lines-MA-n0Hi3Wyg.mp4
5.6 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/25. Welcome to the End of Evaluation Lesson-sgFfl-j_oCs.mp4
5.6 MB
Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules-jPGyFgcIvsM.mp4
5.6 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/10. Integrity and Mindset-zCOr3O50gQM.mp4
5.6 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/27. Making Decisions about Uncertain Data-GM8MV0FvCUo.mp4
5.6 MB
Part 16-Module 03-Lesson 02_SQL Joins/13. Motivation for Other JOINs-3qdv1Ojc9Og.mp4
5.6 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-AaLIKufl_mY.mp4
5.6 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/12. Variance Standard Deviation Final Points-vXUgp2375j4.mp4
5.6 MB
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.mp4
5.6 MB
Part 18-Module 04-Lesson 01_Cleaning Data/11. Cleaning For Tidiness -6nMKFhpVCRU.mp4
5.6 MB
Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results-ZFn9xVQ0hD4.mp4
5.6 MB
Part 11-Module 01-Lesson 12_Feature Selection/08. Features != Information-GOrv8faKHV4.mp4
5.5 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/25. L2 05 Lists Methods V1-WXkPm4rv6ng.mp4
5.5 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/10. Calculate SDs-bjk5m0wrj3w.mp4
5.5 MB
Part 11-Module 01-Lesson 16_Tying It All Together/03. End of Content-MFRkl-aXL8I.mp4
5.5 MB
Part 16-Module 03-Lesson 01_Basic SQL/02. Parch Posey Database-JOMI560DgXg.mp4
5.5 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/05. NumPy and Pandas Data Types-seEFuJ-qvlg.mp4
5.5 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/05. NumPy and Pandas Data Types-seEFuJ-qvlg.mp4
5.5 MB
Part 17-Module 01-Lesson 04_Probability/19. Probability Conclusion-dsVKoXymYDU.mp4
5.5 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-DclTt9xqS4s.mp4
5.5 MB
Part 11-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.mp4
5.5 MB
Part 21-Module 01-Lesson 05_Scripting/08. Scripting With Raw Input-Fs9uLV2qfgI.mp4
5.5 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic-htd-vu8q3po.mp4
5.5 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/05. Tabular Formats-5Vq530Lijb0.mp4
5.5 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-3R0LfaKa-fw.mp4
5.5 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-Xo3Le7VTZZM.mp4
5.5 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Common Table Expressions-qtEKO7B8bXQ.mp4
5.5 MB
Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 Solution-kqcuw1qCLEM.mp4
5.5 MB
Part 18-Module 03-Lesson 01_Assessing Data/01. Introduction-4U3nFMf2KEs.mp4
5.5 MB
Part 17-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data-vhl-SADfti8.mp4
5.5 MB
Part 21-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.mp4
5.5 MB
Part 11-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy-b-oE175NJiQ.mp4
5.5 MB
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-UjyPKvNHz4A.mp4
5.5 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/07. What is the Standard Deviation Measuring-IbwUJ3ORZ5s.mp4
5.5 MB
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.mp4
5.4 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/04. XML in Practice-4xsz7OkDJgM.mp4
5.4 MB
Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-5Uon6hUTl8Y.mp4
5.4 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/15. SD of Karma Points per Post-gIR0M2Jxb0k.mp4
5.4 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-rGw4xFsUUqE.mp4
5.4 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-UXLEe6bNpM4.mp4
5.4 MB
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.mp4
5.4 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/13. Series Indexes-RK6CPtXdK5Q.mp4
5.4 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/14. Series Indexes-RK6CPtXdK5Q.mp4
5.4 MB
Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-M_8000Yz_DA.mp4
5.4 MB
Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.mp4
5.4 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-K6zJtrTEf6k.mp4
5.4 MB
Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-5j6VZr8sHo8.mp4
5.4 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/03. Tetrahedral Die-l7p3uldaCks.mp4
5.4 MB
Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-kjk--LHqtCw.mp4
5.4 MB
Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-_bnZEnWWqXQ.mp4
5.4 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/01. Compare Sample Means-QheTapjHFdU.mp4
5.4 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/10. Details of the Data Science Process-8TeiMKUmoYQ.mp4
5.4 MB
Part 05-Module 01-Lesson 05_Data Quality/16. Auditing Consistency-bCAkWxApvQM.mp4
5.4 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/12. Example Details-aR6Z7ggnjEY.mp4
5.4 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/25. Aggregations-ADx1x2ljFB4.mp4
5.4 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/14. Loading Data with Nested Functions-ME6F4Nyjv8o.mp4
5.4 MB
Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-3r8OR2yQ-KI.mp4
5.4 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/29. Decision Errors-TJ_p0xBI9bI.mp4
5.3 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-e6pJfNbQEKk.mp4
5.3 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/03. Setting Up Hypotheses - Part I-NpZxJg4S6X4.mp4
5.3 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/06. CSVs in Python-YIDH9HBY3Qk.mp4
5.3 MB
Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-rNR4_JqCEuk.mp4
5.3 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/06. Accessing Elements of a DataFrame-4RmQYWI8lY4.mp4
5.3 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/06. Accessing Elements of a DataFrame-4RmQYWI8lY4.mp4
5.3 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-cJCx-Su6vx0.mp4
5.3 MB
Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-eAKVYAR_VlY.mp4
5.3 MB
Part 16-Module 03-Lesson 01_Basic SQL/11. SELECT FROM Statements-urOYuuav4BY.mp4
5.3 MB
Part 18-Module 02-Lesson 01_Gathering Data/22. SELECT FROM Statements-urOYuuav4BY.mp4
5.3 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/26. Evaluation Mini-Project Video-s13K9G1VaWM.mp4
5.3 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/13. SD of Sampling Distribution-tPVKll2xFUw.mp4
5.3 MB
Part 11-Module 01-Lesson 04_Decision Trees/21. Information Gain-KYieR9y-ue4.mp4
5.3 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-cUDZ1vkmdnk.mp4
5.3 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-L9-lBQbknp0.mp4
5.3 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/01. Lesson Introduction-nQBbywNKTVc.mp4
5.3 MB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/08. 24. Classical Music-3hSAWKrdO5s.mp4
5.3 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction to Data Wrangling-4cFsT9KBRs8.mp4
5.3 MB
Part 05-Module 02-Lesson 01_Data and Tables/07. Anatomy of a Table-PhvA7DCgtpw.mp4
5.3 MB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/10. Worst Case and Approximation-ZYcmui02J40.mp4
5.3 MB
Part 05-Module 02-Lesson 01_Data and Tables/02. What's a Database - Intro to Relational Databases-V4gbPVdUOpw.mp4
5.3 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.mp4
5.3 MB
Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-nqMT8qTmQPY.mp4
5.3 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.mp4
5.3 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.mp4
5.3 MB
Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.mp4
5.3 MB
Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules Part II-aASigWQ_XU0.mp4
5.2 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/12. Unpopular-FQoVv3o8vQg.mp4
5.2 MB
Part 13-Module 01-Lesson 04_Design Principles/08. Unemployment Line Plot-EbD9ufptNd0.mp4
5.2 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-7lKhG9bIMhs.mp4
5.2 MB
Part 03-Module 01-Lesson 11_L4 Variability/10. IQR-9dYN_oIly9I.mp4
5.2 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/30. Code Structure and JavaScript-vPCDvEOjP7c.mp4
5.2 MB
Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI-guhmjr4BqSo.mp4
5.2 MB
Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6-eqFgLu0eqBE.mp4
5.2 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/05. SD for Meal Price-PPcSvB1htPc.mp4
5.2 MB
Part 03-Module 01-Lesson 11_L4 Variability/06. Mark Z the Outlier-SADDVcUMQXM.mp4
5.2 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs-PXHHbaYnciY.mp4
5.2 MB
Part 13-Module 01-Lesson 07_Narrative Structures/18. Author-driven Examples-mr2HGcqk3nU.mp4
5.2 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/28. Rent - Find CI-EZTRb9VBqAc.mp4
5.2 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Intro -FnUrE4dhgh8.mp4
5.2 MB
Part 18-Module 04-Lesson 01_Cleaning Data/20. Conclusion -d_nKtLo5WYA.mp4
5.2 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-FNKRumSym18.mp4
5.2 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value-qrN5FQdm9uA.mp4
5.1 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/23. Making Histograms-0J5lNTGbspg.mp4
5.1 MB
Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-gBdKhmtrtG8.mp4
5.1 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.mp4
5.1 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above-lGHZ4w8UqIk.mp4
5.1 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/21. Working with Outliers-4RnQjtJB8t8.mp4
5.1 MB
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-hAPJsh81L98.mp4
5.1 MB
Part 18-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python-KS6cKoKe8ms.mp4
5.1 MB
Part 19-Module 01-Lesson 02_Design/14. Designing for Color Blindness-k4iTzS7t2U4.mp4
5.1 MB
Part 11-Module 01-Lesson 16_Tying It All Together/02. Summary-avqZaTECZTQ.mp4
5.1 MB
Part 03-Module 01-Lesson 20_L8 Estimation/02. Mean of Treated Population-ecy3VY8eNGM.mp4
5.1 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.mp4
5.1 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.mp4
5.1 MB
Part 13-Module 01-Lesson 05_Dimple.js/11. Chart Layout and Group Tags--2yj49s7v5w.mp4
5.1 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.mp4
5.1 MB
Part 03-Module 01-Lesson 11_L4 Variability/29. One Dimension-kPlyl6JlLjY.mp4
5.1 MB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/04. Knapsack Problem--xRKazHGtjU.mp4
5.1 MB
Part 07-Module 01-Lesson 01_GitHub Review/16. Outro-dps7Ti6Lado.mp4
5.1 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/10. Report CI Results 2-eVTzjsolEwI.mp4
5.1 MB
Part 13-Module 01-Lesson 04_Design Principles/40. Lie Factor-jkR2kIJrvBM.mp4
5.1 MB
Part 09-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.mp4
5.1 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/22. L2 07 Lists And Membership Operators II V3-3Nj-b-ZzqH8.mp4
5.1 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-sS-lw3LxATY.mp4
5.1 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/11. Acne Medication-Xt2k2PWBwm4.mp4
5.1 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/19. What is Notation-MaHV5cKfcmE.mp4
5.1 MB
Part 11-Module 01-Lesson 03_SVM/11. SVM Decision Boundary-8hEjeR0qLnA.mp4
5.0 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/05. Intro to CSVs-UFiJYYPL95g.mp4
5.0 MB
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.mp4
5.0 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/20. When Does the CLT Not Work-uZGTVUEMfrU.mp4
5.0 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.mp4
5.0 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.mp4
5.0 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-mZgPfxFOFRE.mp4
5.0 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-mPN46IqnT1c.mp4
5.0 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1-mUfrDUEEa_k.mp4
5.0 MB
Part 18-Module 02-Lesson 01_Gathering Data/01. Introduction-XtJN72lBo94.mp4
5.0 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/10. Less than 240-xUkquw-73BY.mp4
5.0 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision-tSZJDW3qp_I.mp4
5.0 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/23. Wrap-Up-DZa6UOGet_g.mp4
5.0 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test-zqj1NZbe5os.mp4
5.0 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/03. Fitting A Multiple Linear Regression Model-EZNvBF66_b0.mp4
5.0 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/18. Comparing Two Samples-kaVG7U0rda8.mp4
5.0 MB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/02. Data Overview-u_qB4w4kL1o.mp4
5.0 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/28. Probability of Obtaining Mean-00SWFc0sFIg.mp4
5.0 MB
Part 05-Module 02-Lesson 03_Elements of SQL/01. SQL is for Elephants-BYAyquwZmdM.mp4
5.0 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes-FxF9WyIPFbo.mp4
5.0 MB
Part 11-Module 01-Lesson 09_Clustering/17. Clustering Mini-Project Video-68EGMItJiNM.mp4
5.0 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI-diHsJPQHtKc.mp4
5.0 MB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/09. Notation Continued-ZeGnkrKZWBQ.mp4
5.0 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-90OMETgfDyk.mp4
5.0 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-90OMETgfDyk.mp4
5.0 MB
Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files from the Internet-UceKUJ07Bn8.mp4
5.0 MB
Part 13-Module 01-Lesson 07_Narrative Structures/53. Inspecting Accessor Functions-bRkkMdkkFQw.mp4
5.0 MB
Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-LwazT9KH76w.mp4
5.0 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/10. Calculate SDs-x-VMDl-3p7M.mp4
4.9 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/20. Standard Error When n Increases-dU3LgB8i6XM.mp4
4.9 MB
Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.mp4
4.9 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-dtnjREsGfXI.mp4
4.9 MB
Part 03-Module 01-Lesson 11_L4 Variability/07. Chop Off the Tails-NmlhFjNHmXc.mp4
4.9 MB
Part 18-Module 02-Lesson 01_Gathering Data/08. Source Scraping Webpages-ZqTad6Usf9g.mp4
4.9 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/11. Multiple Field Queries-tsAh4HonzIw.mp4
4.9 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/11. Data Vis in Data Science-e_-61K3jK1Y.mp4
4.9 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-Ig82ol_4Lgo.mp4
4.9 MB
Part 19-Module 01-Lesson 02_Design/19. Same Data Different Stories-jSSnkz3QT5Y.mp4
4.9 MB
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.mp4
4.9 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.mp4
4.9 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/40. Smoothing the Animation with Transitions-9c8he26k_iY.mp4
4.9 MB
Part 11-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro-rR68JXwKBxE.mp4
4.9 MB
Part 13-Module 01-Lesson 04_Design Principles/04. Chart Types-0a5oJR6TwAs.mp4
4.9 MB
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-4Fkfu37el_k.mp4
4.9 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/02. Sampling To Distributions To Confidence Intervals-QYMLkDToigc.mp4
4.9 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-Uf_KdjVT2Xg.mp4
4.9 MB
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-Uf_KdjVT2Xg.mp4
4.9 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.mp4
4.9 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.mp4
4.9 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.mp4
4.9 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.mp4
4.9 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/01. Introduction-wwzSxJvGwf0.mp4
4.9 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/01. Introduction-wwzSxJvGwf0.mp4
4.9 MB
Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-xU84TShi7I4.mp4
4.9 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.mp4
4.9 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.mp4
4.9 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/09. Pandas Axis Names-8vr8KQuJLcQ.mp4
4.9 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/09. Pandas Axis Names-8vr8KQuJLcQ.mp4
4.9 MB
Part 11-Module 01-Lesson 07_Regressions/30. R Squared Metric for Regression-yDJEP-XSWdU.mp4
4.9 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/27. Rent - CI-QXFudvtcjv0.mp4
4.9 MB
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.mp4
4.8 MB
Part 05-Module 02-Lesson 01_Data and Tables/11. Favorite Animals-O7kWdC8ffEw.mp4
4.8 MB
Part 13-Module 01-Lesson 04_Design Principles/03. Parts of Speech Analogy for Data Vis-bO8clma7Mnc.mp4
4.8 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-t0yIetl9ZxI.mp4
4.8 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-WCcnGQY771c.mp4
4.8 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-WCcnGQY771c.mp4
4.8 MB
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.mp4
4.8 MB
Part 18-Module 02-Lesson 01_Gathering Data/11. Flashforward 1-Sr5v0i9m_sw.mp4
4.8 MB
Part 12-Module 02-Lesson 05_Trees/09. Insert-j6PkPa2ZHWg.mp4
4.8 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/02. Download Tableau Public-2bXsg6SKHG8.mp4
4.8 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/02. Download Tableau Public-2bXsg6SKHG8.mp4
4.8 MB
Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.mp4
4.8 MB
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.mp4
4.8 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/10. Inspect GeoJSON-ThA4r4nzyj4.mp4
4.8 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/03. Projects and Progress-Z9ZLMQWsbsk.mp4
4.8 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/11. Bounds of Area-eADm6bXU3_0.mp4
4.8 MB
Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-XZNKM3xMZNY.mp4
4.8 MB
Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.mp4
4.8 MB
Part 13-Module 01-Lesson 07_Narrative Structures/38. Communicating Your Message-wZt6fXEUqQM.mp4
4.8 MB
Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-wl3gjMMrYwM.mp4
4.8 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/26. Recap-VM6GGNC2q8I.mp4
4.8 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Programmatic Data Cleaning Process-9-T1CFuOqdQ.mp4
4.8 MB
Part 13-Module 01-Lesson 04_Design Principles/09. Chart Suggestions-5V109AVr_JE.mp4
4.8 MB
Part 13-Module 01-Lesson 04_Design Principles/20. Negative Space-3toURbAUt9s.mp4
4.8 MB
Part 13-Module 01-Lesson 07_Narrative Structures/43. D3 Parsing Dates and Times-DrOoJJWRAno.mp4
4.8 MB
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.mp4
4.8 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-CuMPjPESfY0.mp4
4.8 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/26. DATE Functions Part II-UPWkDhW4cLI.mp4
4.8 MB
Part 18-Module 03-Lesson 01_Assessing Data/06. Types vs. Steps -oZmndg-BnPk.mp4
4.8 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-wBduq7St2Ak.mp4
4.8 MB
Part 13-Module 01-Lesson 04_Design Principles/30. Color Blind-mmw24xSEB3A.mp4
4.8 MB
Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.mp4
4.8 MB
Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-aseCJf5mrdo.mp4
4.8 MB
Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-pX849ta6kaI.mp4
4.8 MB
Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.mp4
4.8 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above-CoFbRt4icdQ.mp4
4.8 MB
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.mp4
4.7 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/16. Drawing Conclusions-s-4ghG9vrGQ.mp4
4.7 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/18. Roll 5 Dice-GVoO-G6g3i0.mp4
4.7 MB
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.mp4
4.7 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/02. Tableau Desktop Download-End96VkLQc4.mp4
4.7 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/02. Tableau Desktop Download-End96VkLQc4.mp4
4.7 MB
Part 16-Module 03-Lesson 01_Basic SQL/24. WHERE Statements -mN0uTnlXaxg.mp4
4.7 MB
Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.mp4
4.7 MB
Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-CPDMSJEH16s.mp4
4.7 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.mp4
4.7 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.mp4
4.7 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.mp4
4.7 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.mp4
4.7 MB
Part 12-Module 02-Lesson 05_Trees/05. Tree Traversal-KZOdmzypynw.mp4
4.7 MB
Part 21-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.mp4
4.7 MB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/03. Choose Your Own Adventure-Ka9nwD0QzTI.mp4
4.7 MB
Part 13-Module 01-Lesson 07_Narrative Structures/41. Parsing Data Before the Draw Function-WALbqgiDHNI.mp4
4.7 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/22. Random Observed Values-KFIt2OC3wCI.mp4
4.7 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-28iU6GrDVfU.mp4
4.7 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/08. Data Visualization and You-m_nSthII_IE.mp4
4.7 MB
Part 05-Module 02-Lesson 03_Elements of SQL/16. Wrap Up-BGt2DQer6I4.mp4
4.7 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots-AtmfksGs-0I.mp4
4.7 MB
Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.mp4
4.7 MB
Part 13-Module 01-Lesson 04_Design Principles/45. The Grammar of Graphics-AdRbdZhLn04.mp4
4.7 MB
Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.mp4
4.7 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.mp4
4.7 MB
Part 11-Module 01-Lesson 13_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.mp4
4.7 MB
Part 11-Module 01-Lesson 04_Decision Trees/15. Formula of Entropy-NHAatuG0T3Q.mp4
4.7 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Im9nOwm_fS8.mp4
4.6 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/22. Popular Chris-cRb2ONJAvog.mp4
4.6 MB
Part 13-Module 01-Lesson 04_Design Principles/34. Determining a Graphic's Effectiveness-BZERcWwQ-PM.mp4
4.6 MB
Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.mp4
4.6 MB
Part 17-Module 01-Lesson 07_Bayes Rule/32. Reducing Uncertainty-zuFMhmKQ--o.mp4
4.6 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/09. How Does Project Submission Work-jCJa_VP6qgg.mp4
4.6 MB
Part 13-Module 01-Lesson 04_Design Principles/50. Grammar of Graphics and D3 Functions-rADl_md-WNM.mp4
4.6 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/11. In-Place vs. Not In-Place-STqN_v6Iz5o.mp4
4.6 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place-STqN_v6Iz5o.mp4
4.6 MB
Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-WZRsqdNrC1A.mp4
4.6 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/32. Hypothesis Testing Conclusion-nQFchD4XPPs.mp4
4.6 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/04. 29 Number Summary-gzUN5zKLHjQ.mp4
4.6 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/16. Type And Quality Plot - Part 1-iRCS1sE78KI.mp4
4.6 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-FLpXmoHp7eE.mp4
4.6 MB
Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-FLpXmoHp7eE.mp4
4.6 MB
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.mp4
4.6 MB
Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.mp4
4.6 MB
Part 13-Module 01-Lesson 07_Narrative Structures/26. Thinking with Joins-HGQ25_ivLMQ.mp4
4.5 MB
Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-FORb9Tja-p0.mp4
4.5 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots--gIxCjLXCEs.mp4
4.5 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/03. Your First Subquery-cTM1jPYXLoQ.mp4
4.5 MB
Part 09-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer-SsNYXdi3q-I.mp4
4.5 MB
Part 13-Module 01-Lesson 05_Dimple.js/06. Dimple Bar Chart Code Overview-vuxN6EC_gso.mp4
4.5 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/31. Lesson Conclusion-quP9Njc2aMg.mp4
4.5 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-XCf2FDdHDGs.mp4
4.5 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-2yo4xrFnDyg.mp4
4.5 MB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML Structure-UjCbXQ8Coic.mp4
4.5 MB
Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-sbQXPn9xLvI.mp4
4.5 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/18. Recreating China's Red Dot-tDRHSTivs4k.mp4
4.5 MB
Part 18-Module 02-Lesson 01_Gathering Data/05. Source Files On Hand-PjP-EaeXTiY.mp4
4.5 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/28. Probability of Obtaining Mean-ErwocwQVgYE.mp4
4.5 MB
Part 11-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.mp4
4.5 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/16. Precision and Recall-3vT0kSBCLdU.mp4
4.5 MB
Part 17-Module 01-Lesson 16_Logistic Regression/20. Precision and Recall-3vT0kSBCLdU.mp4
4.5 MB
Part 12-Module 02-Lesson 05_Trees/15. Heaps-M3B0UJWS_ag.mp4
4.5 MB
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.mp4
4.5 MB
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.mp4
4.5 MB
Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results-l_HFnHve3Ok.mp4
4.5 MB
Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-N6hiygoT9FE.mp4
4.5 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. Performance Tuning 1-5mVfYZ_bfRo.mp4
4.5 MB
Part 21-Module 01-Lesson 05_Scripting/13. Handling Errors Try Except Finally-S6hwBZG0KwM.mp4
4.4 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values-e2C4tEKNtqs.mp4
4.4 MB
Part 21-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.mp4
4.4 MB
Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-FT0dM2um34E.mp4
4.4 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/18. Combining Pandas DataFrames-vB_Et1hz_2M.mp4
4.4 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/18. Combining Pandas DataFrames-vB_Et1hz_2M.mp4
4.4 MB
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.mp4
4.4 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-FpcCdcKFBKM.mp4
4.4 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/18. Finches - Find t-Statistic-eAN4NfHSgk8.mp4
4.4 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/22. Bootstrapping-42j3YclcZ4Q.mp4
4.4 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-cUlEryXX9BM.mp4
4.4 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions-szqkEhERjDI.mp4
4.4 MB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/02. Cleaning with String Functions-y1fduSu7Ovc.mp4
4.4 MB
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.mp4
4.4 MB
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.mp4
4.4 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators-48AgxPygRuQ.mp4
4.4 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values-kNsdYqgn9Mk.mp4
4.4 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/41. The World Cup Narrative-nnqZR2GdcAA.mp4
4.4 MB
Part 17-Module 01-Lesson 04_Probability/01. Introduction to Probability-HeoQccoqfTk.mp4
4.4 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/35. L2 01 Compound Data Structures V1-jmQ8IKvQgBU.mp4
4.4 MB
Part 17-Module 01-Lesson 14_Regression/17. How Do We Know If Our Model Fits Well-0vPtPAqMHJE.mp4
4.4 MB
Part 12-Module 02-Lesson 06_Graphs/07. Adjacency Matrices-FsFhoTALA1c.mp4
4.4 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/21. Great Job!-fm66AGJzRI0.mp4
4.4 MB
Part 12-Module 02-Lesson 04_Maps and Hashing/09. String Keys-WyFwieF1NN4.mp4
4.4 MB
Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-ieiQqLicBjg.mp4
4.4 MB
Part 16-Module 03-Lesson 02_SQL Joins/01. Introduction to JOINs-YvZ010GU-Ck.mp4
4.4 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-8QEAYYIyopY.mp4
4.4 MB
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-8QEAYYIyopY.mp4
4.4 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/14. Other Sampling Distributions-Bxl0DonzX8c.mp4
4.4 MB
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.mp4
4.4 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01-9EFRrU4WBs4.mp4
4.4 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/04. Business Example-Wzz7omSDfEk.mp4
4.4 MB
Part 03-Module 01-Lesson 11_L4 Variability/28. Avg. Squared Dev. in Words-kgc_y-oJObM.mp4
4.4 MB
Part 06-Module 01-Lesson 03_Analyzing Data/20. Congrats-quszTmIRG8M.mp4
4.4 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-WjRAjbeG0RE.mp4
4.4 MB
Part 11-Module 01-Lesson 07_Regressions/21. Linear Regression Errors-A4nPMEOcUd4.mp4
4.4 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/15. Two Useful Theorems-jQ5i7CALdRQ.mp4
4.4 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/07. Google Account-7C3vCAVaPXo.mp4
4.4 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/07. Google Account-7C3vCAVaPXo.mp4
4.4 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-QII0tSAIex0.mp4
4.4 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/18. Roll 5 Dice-BgBEqvjLNig.mp4
4.4 MB
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.mp4
4.4 MB
Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD-UbnrfnB8vcs.mp4
4.3 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs-Zw3X9BQQKB0.mp4
4.3 MB
Part 13-Module 01-Lesson 07_Narrative Structures/61. I am Legend-EdiM9XCqc0Y.mp4
4.3 MB
Part 12-Module 02-Lesson 05_Trees/03. Tree Terminology-mPUsDUR_sj8.mp4
4.3 MB
Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-aveIz1JYeAg.mp4
4.3 MB
Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-CJ_C0FZBCPY.mp4
4.3 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes-icmKCnOXQdI.mp4
4.3 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-Keh5GwaSWdk.mp4
4.3 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-ClkOE3kdvLs.mp4
4.3 MB
Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ujpjeaxE6GU.mp4
4.3 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/01. Interview Introduction-dRsHYt1Lddc.mp4
4.3 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-pUaHzMlfxrk.mp4
4.3 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-hW_1ASU-j8A.mp4
4.3 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-GGCzMmOpQqQ.mp4
4.3 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Why Are Sampling Distributions Important-aDFDOCJKoH0.mp4
4.3 MB
Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.mp4
4.3 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/07. More Detail-E931DQC0hno.mp4
4.3 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/30. Hot Beverage-0O_5vNJycJg.mp4
4.3 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.mp4
4.3 MB
Part 11-Module 01-Lesson 06_Datasets and Questions/11. Enron Dataset Mini-Project Video-0zGp5er3fy4.mp4
4.3 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/14. Adding a DataFrame to a Series-K2sUmPodhqg.mp4
4.2 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/14. Adding a DataFrame to a Series-K2sUmPodhqg.mp4
4.2 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.mp4
4.2 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/07. Univariate Plots-kgmYLreYB0A.mp4
4.2 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/28. Klout Sampling Distribution (Mean)-8o5Elsb2pFY.mp4
4.2 MB
Part 13-Module 01-Lesson 07_Narrative Structures/62. Adding Circles to the Legend-FlbCPYGCKqk.mp4
4.2 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1 Solution -I1enB5CA85Q.mp4
4.2 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/02. Why Do We Use Data Visualizations-iiOP4PE46f4.mp4
4.2 MB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/04. Element-wise Matrix Operations-vjUykZyzko4.mp4
4.2 MB
Part 21-Module 01-Lesson 01_Why Python Programming/03. L1 03 Programming In Python V4-O1cTNYAjeeg.mp4
4.2 MB
Part 18-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces)-1y_qjUMDsCw.mp4
4.2 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-WGD8AWQg9dE.mp4
4.2 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/23. Drawing Conclusions Example-yAl58ccwyvU.mp4
4.2 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/06. Appending And NumPy-fdpKvovBMe4.mp4
4.2 MB
Part 11-Module 01-Lesson 08_Outliers/08. Outliers Mini-Project Video-GRN0Whyy4Lk.mp4
4.2 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-lK2lDLdE6iA.mp4
4.2 MB
Part 13-Module 01-Lesson 07_Narrative Structures/39. Using extent() for scales-oazLw2JhKiU.mp4
4.2 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -CSW2i2jIqyA.mp4
4.2 MB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML File Structure -4ef_Dr_SXTw.mp4
4.2 MB
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.mp4
4.2 MB
Part 11-Module 01-Lesson 07_Regressions/11. Slope and Intercept-Ksn1g5fCe1I.mp4
4.2 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/17. Find Standard Error-ctx--oGjVgs.mp4
4.2 MB
Part 07-Module 01-Lesson 01_GitHub Review/06. Quick Fixes-Lb9e2KemR6I.mp4
4.2 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Introduction to Summary Statistics-PCZmHCrcMcw.mp4
4.2 MB
Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.mp4
4.2 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test-bD9ULWEsW0M.mp4
4.2 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations-q5PjL9GkVtM.mp4
4.2 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations-q5PjL9GkVtM.mp4
4.2 MB
Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-2ieszOqnpWs.mp4
4.2 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/27. L2 04 Tuples V3-33xN-AbTMoc.mp4
4.2 MB
Part 13-Module 01-Lesson 04_Design Principles/28. How Visualizations can Save Lives-VUllIatQ3tI.mp4
4.1 MB
Part 16-Module 03-Lesson 02_SQL Joins/02. Why Use Separate Tables-UIQBtpmqYOs.mp4
4.1 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/12. Gathering Data-JsVg95-amjI.mp4
4.1 MB
Part 09-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.mp4
4.1 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data-D7m25cvqUpw.mp4
4.1 MB
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-E63RZli2F2o.mp4
4.1 MB
Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.mp4
4.1 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/39. Keyboards - CI for Dependent Samples-83VGOXwmjUw.mp4
4.1 MB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/17. Conclusion-D_ioSXAre1A.mp4
4.1 MB
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.mp4
4.1 MB
Part 16-Module 03-Lesson 01_Basic SQL/06. Why Do Analysts Like SQL-uCNOtUht2Xc.mp4
4.1 MB
Part 18-Module 02-Lesson 01_Gathering Data/22. Why Do Analysts Like SQL-uCNOtUht2Xc.mp4
4.1 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/12. Types Of Errors - Part III-Z-srkCPsdaM.mp4
4.1 MB
Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance--5--eKjgU7k.mp4
4.1 MB
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.mp4
4.1 MB
Part 12-Module 02-Lesson 06_Graphs/10. DFS-BC8jEidd2EQ.mp4
4.1 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/16. How Do We Choose Between Hypotheses-JkXTwS-5Daw.mp4
4.1 MB
Part 12-Module 02-Lesson 05_Trees/18. Self-Balancing Trees-EHI548K3jiw.mp4
4.1 MB
Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.mp4
4.1 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-NcWS_BvM3IU.mp4
4.1 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-plnMY4iATyU.mp4
4.1 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-mIzPoh_kqw4.mp4
4.1 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/07. Metric - Click Through Rate-EpfoKAwV_Eg.mp4
4.1 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/21. One tailed or two tailed-Cf8PvkUR1NQ.mp4
4.1 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-Z4n3jR-FZP8.mp4
4.1 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/11. Traditional vs. Bootstrapping Confidence Intervals-eZ8lyiumXDY.mp4
4.1 MB
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.mp4
4.1 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-ta5Nz-YCn6g.mp4
4.1 MB
Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-xJtmPbEfpFo.mp4
4.1 MB
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-PRjmvj6Vubs.mp4
4.1 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.mp4
4.1 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/25. DATE Functions I-E7Z6GMFVmIY.mp4
4.0 MB
Part 03-Module 01-Lesson 11_L4 Variability/08. Where Is Q1-eLyI7n6GtbU.mp4
4.0 MB
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.mp4
4.0 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/01. Intro to Creating Tables-mIIL-p2gaK4.mp4
4.0 MB
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.mp4
4.0 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.mp4
4.0 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/22. Outliers Advice-BhhDoTgYQmI.mp4
4.0 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/37. setInterval and clearInterval-r1sgfqg85us.mp4
4.0 MB
Part 17-Module 01-Lesson 08_Python Probability Practice/02. Simulating Coin Flips-7YtQNZ3iy6o.mp4
4.0 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/02. NULLs-WYUkLKn6XCw.mp4
4.0 MB
Part 18-Module 02-Lesson 01_Gathering Data/21. Storing Data-hcosH34b-yw.mp4
4.0 MB
Part 18-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -exMGBx6Rs_E.mp4
4.0 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.mp4
4.0 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.mp4
4.0 MB
Part 13-Module 01-Lesson 04_Design Principles/52. The Purpose of the Grammar of Graphics-pZyrfzuB5FE.mp4
4.0 MB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/05. Cleaning With More Advanced String Functions-E6cK8RbYGEc.mp4
4.0 MB
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.mp4
4.0 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/18. Finches - Find t-Statistic-nBqsiW5r-98.mp4
4.0 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.mp4
4.0 MB
Part 12-Module 02-Lesson 04_Maps and Hashing/05. Hashing-kCPFfHx_LgQ.mp4
4.0 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/08. Continuous vs. Discrete Data-BzgZebZD9kk.mp4
4.0 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Introduction to Window Functions-u3qLjP8KMKc.mp4
4.0 MB
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.mp4
4.0 MB
Part 13-Module 01-Lesson 04_Design Principles/05. Visualizations in Data Science-UCKGGQ4LFjo.mp4
4.0 MB
Part 11-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.mp4
4.0 MB
Part 18-Module 04-Lesson 01_Cleaning Data/08. Addressing Missing Data First -ArAGZCUMj9Q.mp4
4.0 MB
Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.mp4
4.0 MB
Part 11-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.mp4
4.0 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-a1sLkQtfUKc.mp4
4.0 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262-c6PzC3WZD4I.mp4
4.0 MB
Part 18-Module 03-Lesson 01_Assessing Data/10. Assessing Vs Exploring V2 -hVFZ6jFKOso.mp4
4.0 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-6yT3SlcmTl8.mp4
4.0 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/22. Popular Chris-VTgnBeCqHjE.mp4
4.0 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean-potr9cTBlxI.mp4
4.0 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Data in the Real World-HmipezTjTDY.mp4
4.0 MB
Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.mp4
4.0 MB
Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-bcwFahJsww0.mp4
3.9 MB
Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores-8XZqX03Y6Vk.mp4
3.9 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values-l3ergsxocok.mp4
3.9 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values-l3ergsxocok.mp4
3.9 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/17. Simulating From the Null-sL2yJtHZd8Y.mp4
3.9 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-QBaNltqVj_0.mp4
3.9 MB
Part 03-Module 01-Lesson 11_L4 Variability/05. Does Range Change-sCHCU42thsI.mp4
3.9 MB
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.mp4
3.9 MB
Part 11-Module 01-Lesson 10_Feature Scaling/13. Feature Scaling Mini-Project Video-e6zbTFctnJU.mp4
3.9 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision-k1plVVNoyeY.mp4
3.9 MB
Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-1lNAvDubBfI.mp4
3.9 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/03. Sampling Distributions Confidence Intervals-gICzUhMVymo.mp4
3.9 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/20. Hierarchies-wl_AM-spH68.mp4
3.9 MB
Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-nu2OKJwDvvE.mp4
3.9 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.mp4
3.9 MB
Part 03-Module 01-Lesson 11_L4 Variability/21. Be Happy and Get Rid of Negatives-_afLozDIcLw.mp4
3.9 MB
Part 12-Module 02-Lesson 05_Trees/20. Tree Rotations-O5Yl-m0YbVA.mp4
3.9 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby-aWc18hHpXRk.mp4
3.9 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-kFKsCAyiPuY.mp4
3.9 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-kFKsCAyiPuY.mp4
3.9 MB
Part 07-Module 01-Lesson 01_GitHub Review/03. Good GitHub repository-qBi8Q1EJdfQ.mp4
3.9 MB
Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-JZx1Pyzuo_s.mp4
3.9 MB
Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-vsID16a_suU.mp4
3.9 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.mp4
3.9 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-FdRVdkASudw.mp4
3.9 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/11. Report Results Effect Size-jjByXJIiCLs.mp4
3.9 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center-CBaw2pGOO3A.mp4
3.9 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2-cpDTPUNDo4U.mp4
3.9 MB
Part 09-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data-8FD_iOP24UA.mp4
3.9 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.mp4
3.9 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-RIJpz1jXO4A.mp4
3.9 MB
Part 12-Module 02-Lesson 05_Trees/12. BSTs-abRNGLhGUmE.mp4
3.9 MB
Part 12-Module 02-Lesson 06_Graphs/11. BFS-pol4kGNlvJA.mp4
3.9 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Window Functions-gp0RPgkDHsQ.mp4
3.9 MB
Part 17-Module 01-Lesson 14_Regression/16. How Do We Interpret Results-eLk0XGGMaCE.mp4
3.9 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/03. Tetrahedral Die-WtGcIl_o_40.mp4
3.9 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.mp4
3.9 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.mp4
3.8 MB
Part 18-Module 03-Lesson 01_Assessing Data/22. Outro -lfWT0kLfe8c.mp4
3.8 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -Y288CGrwGy4.mp4
3.8 MB
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.mp4
3.8 MB
Part 09-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.mp4
3.8 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/26. Predicting Based on Many Features-oZqGlJbRZu4.mp4
3.8 MB
Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-PXNaLWJ5SKg.mp4
3.8 MB
Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error-w-7MoreKqaU.mp4
3.8 MB
Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-Nmf80xB1DN0.mp4
3.8 MB
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.mp4
3.8 MB
Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-eeV5K5HKVx4.mp4
3.8 MB
Part 05-Module 02-Lesson 01_Data and Tables/17. Summary-1Gp4l-ZTCVk.mp4
3.8 MB
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.mp4
3.8 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-3uUwfgOUT0Y.mp4
3.8 MB
Part 05-Module 02-Lesson 03_Elements of SQL/10. Why Do It in the Database-6vfZYhhmuLU.mp4
3.8 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/23. Critical Values 0.05-P-CGd_Vzpk0.mp4
3.8 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/20. Calculating the p-value-_W3Jg7jQ8jI.mp4
3.8 MB
Part 16-Module 03-Lesson 01_Basic SQL/09. Types Of Statements-vLvJbIz94C4.mp4
3.8 MB
Part 18-Module 02-Lesson 01_Gathering Data/22. Types Of Statements-vLvJbIz94C4.mp4
3.8 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/29. Why D3-2qZ3d2WOvwE.mp4
3.8 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-xBnhUJENAtk.mp4
3.8 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/07. Significance-FGtU7YDLX2Y.mp4
3.8 MB
Part 12-Module 02-Lesson 06_Graphs/03. Directions and Cycles-lF0vUktQDPo.mp4
3.8 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size-kKT56up4n_o.mp4
3.8 MB
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.mp4
3.8 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/45. Fixing the Buttons-NxM_iu4sDxw.mp4
3.8 MB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/11. CAST-LbyOq4ofLng.mp4
3.8 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Solution -lJEMTES2Ar8.mp4
3.8 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-6BBUSWrSuFA.mp4
3.8 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/14. Performance Tuning Motivation-aY4_uYWEuoE.mp4
3.8 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/32. Location of Mean on Distribution-k3RUgrtFIl4.mp4
3.8 MB
Part 13-Module 01-Lesson 07_Narrative Structures/63. Adding Text to the Legend-VPI9MVqGiSM.mp4
3.8 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/06. Accessing Elements of a DataFrame-hZp9cVuiPo0.mp4
3.8 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/06. Accessing Elements of a DataFrame-hZp9cVuiPo0.mp4
3.8 MB
Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-80aFO4KmcPM.mp4
3.8 MB
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.mp4
3.8 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post-NtldeU_E4sI.mp4
3.8 MB
Part 11-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.mp4
3.7 MB
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-Ee2o-0arldg.mp4
3.7 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/06. DF - Marginal Totals-ykVKAjC9_TA.mp4
3.7 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.mp4
3.7 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/07. Working In The JavaScript Console-cj4kv_dtqY0.mp4
3.7 MB
Part 05-Module 02-Lesson 01_Data and Tables/06. Zoo-YG8zfeRXAvM.mp4
3.7 MB
Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment Solution-LhdGQC_vjEs.mp4
3.7 MB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/01. Introduction to Data Cleaning-YTtH3NM2BX0.mp4
3.7 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values-coHA_ziMiws.mp4
3.7 MB
Part 13-Module 01-Lesson 07_Narrative Structures/55. Attendance at Every World Cup Game-LuCV0YuhoZE.mp4
3.7 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs-CtbwhKXSEMs.mp4
3.7 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.mp4
3.7 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/06. Example of Sampling Distributions - Part I-1XezzP6kxUE.mp4
3.7 MB
Part 18-Module 02-Lesson 01_Gathering Data/27. Conclusion-IanoSiET2nA.mp4
3.7 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/12. Affect t-Statistic-HMfd6rQrI0Y.mp4
3.7 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/05. DF - Add to 10-MxLG3eGzkI8.mp4
3.7 MB
Part 13-Module 01-Lesson 07_Narrative Structures/47. Creating Axes-3jEbyeW1Re4.mp4
3.7 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/04. Further Motivation-sjGxUKrbKoI.mp4
3.7 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.mp4
3.7 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/39. Update the Title-ut83yNUYLmc.mp4
3.7 MB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML and Trees-766JMEtZCPE.mp4
3.7 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-DIrLvDqhjCg.mp4
3.7 MB
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.mp4
3.7 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/17. Why Data Dashboards-8ni2lCqAVvQ.mp4
3.7 MB
Part 12-Module 02-Lesson 05_Trees/19. Red-Black Trees - Insertion-dIuWLtWnkgs.mp4
3.7 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/14. -z-mXs7Rl-Ys.mp4
3.6 MB
Part 18-Module 03-Lesson 01_Assessing Data/14. Programatic Assessment -Bk_Ve3-4eps.mp4
3.6 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-t_ZSrov187k.mp4
3.6 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. 141 Assess Intro V4-mdrAdtziXh4.mp4
3.6 MB
Part 12-Module 02-Lesson 05_Trees/17. Heap Implementation-2LAdml6_pDY.mp4
3.6 MB
Part 17-Module 01-Lesson 16_Logistic Regression/33. Congrats-Qy8VYdqoxGA.mp4
3.6 MB
Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment -YrX-oiFilyA.mp4
3.6 MB
Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-gUXB5GofFKM.mp4
3.6 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-8LDZzqrCnS0.mp4
3.6 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/22. Comparing the Two Student Groups-eM82u21V7AM.mp4
3.6 MB
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-ZwMY5rAAd7Q.mp4
3.6 MB
Part 17-Module 01-Lesson 14_Regression/06. Scatter Plots -DvlxZ37O4i8.mp4
3.6 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/09. Scatter Plots -DvlxZ37O4i8.mp4
3.6 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.mp4
3.6 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.mp4
3.6 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject-K2OncV6Bzo8.mp4
3.6 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/29. Congrats-psVUIDdsbA0.mp4
3.6 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next-AwpX6HkhL0k.mp4
3.6 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-TU63rBOwXQ8.mp4
3.6 MB
Part 13-Module 01-Lesson 07_Narrative Structures/42. I Love Data Visualization-j24CoLV675I.mp4
3.6 MB
Part 18-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty Messy -WG6mil60jq0.mp4
3.6 MB
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.mp4
3.6 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/13. Worksheets-2xRKvQTRtlk.mp4
3.6 MB
Part 17-Module 01-Lesson 08_Python Probability Practice/04. Simulating Many Coin Flips-AqpWQIj2V5Y.mp4
3.6 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-E3NhvAC3Ghw.mp4
3.6 MB
Part 03-Module 01-Lesson 11_L4 Variability/11. What Is an Outlier-XP3F26GGuhE.mp4
3.6 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-TE2BZql64XY.mp4
3.6 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/33. Adding Bars and Text-EcwO8YPrn-M.mp4
3.6 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.mp4
3.6 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.mp4
3.6 MB
Part 11-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.mp4
3.6 MB
Part 21-Module 01-Lesson 05_Scripting/11. Errors And Exceptions-DmthSiy2d0U.mp4
3.5 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/08. 05 Hierarchies-vkHeQcI08yc.mp4
3.5 MB
Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-Mt5TWGYacJs.mp4
3.5 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/17. Find Standard Error-YNuoRW6EyEo.mp4
3.5 MB
Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-W74CdB_pl5M.mp4
3.5 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/09. -zWNcZ-7k7Tw.mp4
3.5 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.mp4
3.5 MB
Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-PRQDaHphZhw.mp4
3.5 MB
Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-AnksTk1zI3Y.mp4
3.5 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/19. Standard Error for Avg of 5 Dice-RQ_AHYQTSDA.mp4
3.5 MB
Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.mp4
3.5 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-NNE8Cr77ytg.mp4
3.5 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-NNE8Cr77ytg.mp4
3.5 MB
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.mp4
3.5 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic-0iKPoKeApJI.mp4
3.5 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/14. Correct Interpretations of Confidence Intervals-IhYv_SlN7e8.mp4
3.5 MB
Part 07-Module 01-Lesson 01_GitHub Review/02. GitHub profile important items-prvPVTjVkwQ.mp4
3.5 MB
Part 13-Module 01-Lesson 04_Design Principles/16. Charts Types and Design Elements-h2tIZuzMuQU.mp4
3.5 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.mp4
3.5 MB
Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.mp4
3.5 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/01. Instructor Introduction Juno Lee-to8Pp3PCOZo.mp4
3.5 MB
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.mp4
3.5 MB
Part 13-Module 01-Lesson 05_Dimple.js/23. Changing the Date Format-_jOLSNoKxhQ.mp4
3.5 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/30. r^2-mnfgAsAVaTQ.mp4
3.5 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations--InZYjwPsKs.mp4
3.5 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations--InZYjwPsKs.mp4
3.5 MB
Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-iCTPBcowJRY.mp4
3.5 MB
Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-CML5XbavX0w.mp4
3.5 MB
Part 16-Module 03-Lesson 01_Basic SQL/12. Intro To SQL Workspaces-w6XcuK22YCk.mp4
3.5 MB
Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3-o7LnSu0CEb4.mp4
3.5 MB
Part 17-Module 01-Lesson 14_Regression/10. What Defines A Line-lTqwhsSNP2c.mp4
3.5 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/11. Two-Tailed Test-4fWHT1f72B8.mp4
3.5 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/11. Metric - Average Reading Duration-w6Y9ZxHDEbw.mp4
3.5 MB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/09. 25. Caffeine--D3nyKUK1kY.mp4
3.5 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-9L9bhMCHQ-M.mp4
3.5 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/22. NEW D3 Scale Syntax-ba-Luz-Ip0Y.mp4
3.5 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/09. Investigating the Data-zJ_wWRTQUTs.mp4
3.5 MB
Part 07-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2-elZCLxVvJrY.mp4
3.5 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/10. Two-Tailed t-Test-5mxtx0yqlyM.mp4
3.5 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/05. 03 Tableau Interface-q3E4CCYeIyM.mp4
3.5 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-vsLtePFaOFY.mp4
3.5 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-vsLtePFaOFY.mp4
3.5 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.mp4
3.5 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.mp4
3.5 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.mp4
3.4 MB
Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-VEXUQmVpazE.mp4
3.4 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.mp4
3.4 MB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/04. Syntax-08M93RaBSgU.mp4
3.4 MB
Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.mp4
3.4 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-5tdFjuAX9u0.mp4
3.4 MB
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.mp4
3.4 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null-qUcZFxEXz2I.mp4
3.4 MB
Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-zTI5Ci5WWzM.mp4
3.4 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Running Totals And Count-rNJwmnzUTxg.mp4
3.4 MB
Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1-tYaQItpvXUo.mp4
3.4 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/04. Probability Greater-5DZTwMn7GAY.mp4
3.4 MB
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.mp4
3.4 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-J2L_ZU-YMxc.mp4
3.4 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-HH73nOnzRrc.mp4
3.4 MB
Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-TIs9j-QITxw.mp4
3.4 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.mp4
3.4 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Introduction To Notation-ISkBSUVH49M.mp4
3.4 MB
Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-sy_jiSEy-Nw.mp4
3.4 MB
Part 09-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.mp4
3.4 MB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare-B2KnUg5iz0Y.mp4
3.4 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/30. Conclusion-33thdy0IjPE.mp4
3.4 MB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/18. 26. Video Games-SyszPG1615c.mp4
3.4 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/24. There Must Be A Better Way-oBp8YX2AgJw.mp4
3.4 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/01. Introduction to Advanced SQL-i0VaVPIKUks.mp4
3.4 MB
Part 11-Module 01-Lesson 07_Regressions/24. Minimizing Sum of Squared Errors-E1XzT619Eug.mp4
3.4 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-BGNx2FiNFY0.mp4
3.4 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-YetpTU5SmUg.mp4
3.4 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score--Sw8Dlo0fx4.mp4
3.4 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/13. Katie - SDs Below-COHUHzCELK4.mp4
3.4 MB
Part 17-Module 01-Lesson 14_Regression/21. Recap-DzMi27LI5l4.mp4
3.4 MB
Part 11-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.mp4
3.4 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-6K9Zztqbozw.mp4
3.4 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-xE00wGLivN4.mp4
3.4 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/16. -_mge9UU-gpQ.mp4
3.3 MB
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-Kn9v0KGDsvc.mp4
3.3 MB
Part 16-Module 03-Lesson 01_Basic SQL/21. Order By Part II-XQCjREdOqwE.mp4
3.3 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion-SRXNBlvW-xw.mp4
3.3 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends-swOg73wqLKM.mp4
3.3 MB
Part 13-Module 01-Lesson 07_Narrative Structures/59. New Data Stories in the Graphic-9yKFn_R2c_U.mp4
3.3 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-C6okqt-jf08.mp4
3.3 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-C6okqt-jf08.mp4
3.3 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Lv22Usic4A8.mp4
3.3 MB
Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Tp5WCAJiCRY.mp4
3.3 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/17. Shape of Distributions-UnN99AAYf8k.mp4
3.3 MB
Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-_TJeoCTDykE.mp4
3.3 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Aggregates in Window Functions-Dxew5w3VF7k.mp4
3.3 MB
Part 18-Module 02-Lesson 01_Gathering Data/25. You Can Iterate-QsJqoJYhTiw.mp4
3.3 MB
Part 21-Module 01-Lesson 05_Scripting/13. Handling Error Specifying Exceptions-EHW5I7shdJg.mp4
3.3 MB
Part 12-Module 02-Lesson 06_Graphs/13. Eulerian Path-zS34kHSo7fs.mp4
3.3 MB
Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.mp4
3.3 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-lbNk216NW48.mp4
3.3 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-lbNk216NW48.mp4
3.3 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Introduction to Percentiles-t7SX2ZEdxKA.mp4
3.3 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.mp4
3.3 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-E55ujT-kf5E.mp4
3.3 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-OT2aD9XgOWg.mp4
3.3 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-OT2aD9XgOWg.mp4
3.3 MB
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-xYxD4GD1woo.mp4
3.3 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-GwzB76HYlFE.mp4
3.3 MB
Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings-0-LYyC_70jk.mp4
3.3 MB
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-ZULplTNbIIs.mp4
3.3 MB
Part 13-Module 01-Lesson 05_Dimple.js/17. Inspecting the X-axis-huZPg2gRmLk.mp4
3.3 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-QJxhBCWK6BQ.mp4
3.3 MB
Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet II-M0qR7to1fl4.mp4
3.3 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/16. Performance Tuning 2-arMtEhSoq7E.mp4
3.3 MB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview-2X8GJyZUlDo.mp4
3.3 MB
Part 21-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.mp4
3.3 MB
Part 13-Module 01-Lesson 07_Narrative Structures/17. Different Types of Narrative Structures-vTlpDo33ezg.mp4
3.3 MB
Part 13-Module 01-Lesson 04_Design Principles/44. Leland Wilkinson-w7TLo_X4sfY.mp4
3.3 MB
Part 11-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection-S-xe0-XNo4I.mp4
3.2 MB
Part 16-Module 03-Lesson 02_SQL Joins/14. JOINs-CxuHtd1Daqk.mp4
3.2 MB
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-K4gGK4ScT7M.mp4
3.2 MB
Part 11-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project-JEK7-ocWu0M.mp4
3.2 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/15. Nest Function-rwDTbptCnM4.mp4
3.2 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.mp4
3.2 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/10. Theoretical Normal Distribution-vyy5yUt1IrE.mp4
3.2 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/07. Types Of Errors - Part I-aw6GMxIvENc.mp4
3.2 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.mp4
3.2 MB
Part 03-Module 01-Lesson 11_L4 Variability/36. Find Values-fUI1XABUTrY.mp4
3.2 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-zlopUR9utUY.mp4
3.2 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-zlopUR9utUY.mp4
3.2 MB
Part 03-Module 01-Lesson 11_L4 Variability/08. Where Is Q1-0ZTaV6UATBI.mp4
3.2 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-bgT8sWuV2lc.mp4
3.2 MB
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-bgT8sWuV2lc.mp4
3.2 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/15. Who Has More Shoes-ODDruv2Qkdg.mp4
3.2 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/01. t-Distribution-TC2Ro6pFAqA.mp4
3.2 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.mp4
3.2 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size-VXH1be4d1Nc.mp4
3.2 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/19. Congratulations!-_FPpbuuW-1o.mp4
3.2 MB
Part 17-Module 01-Lesson 14_Regression/08. Correlation Coefficients-rL5Bn8Fi-zE.mp4
3.2 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/11. Correlation Coefficients-rL5Bn8Fi-zE.mp4
3.2 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/29. Rent - Margin of Error-nHF7LgYaZnE.mp4
3.2 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/23. The Radius Scale-Rkrj1HjaMQM.mp4
3.2 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Notation for the Mean-3EF15AoRxyM.mp4
3.2 MB
Part 07-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages-_0AHmKkfjTo.mp4
3.2 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/05. Experiment I-JLKAdT2JESk.mp4
3.2 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-7E7Czixpviw.mp4
3.2 MB
Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-aznzJPXavDg.mp4
3.2 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.mp4
3.1 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/24. Are your Results Just Noise-LjuF5M6ymPA.mp4
3.1 MB
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.mp4
3.1 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/30. Conclusion-mjPfjzOWiDw.mp4
3.1 MB
Part 13-Module 01-Lesson 07_Narrative Structures/50. The Anonymous Accessor Function-I4niz8YMMUM.mp4
3.1 MB
Part 12-Module 02-Lesson 02_List-Based Collections/02. Lists-KUQSgUMtyv0.mp4
3.1 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.mp4
3.1 MB
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.mp4
3.1 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-1jUwuW70lF0.mp4
3.1 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/09. Operational Definition-khRQslIcqyY.mp4
3.1 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/09. Operational Definition-khRQslIcqyY.mp4
3.1 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/17. Aggregations-4nGL3y3Nq-0.mp4
3.1 MB
Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-ADNFKiAjmWA.mp4
3.1 MB
Part 13-Module 01-Lesson 07_Narrative Structures/48. Adding the Axes to the Page-B3qrRUamyUs.mp4
3.1 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.mp4
3.1 MB
Part 18-Module 04-Lesson 01_Cleaning Data/04. Manual Vs Programmatic Cleaning -AQFBVQy_HyY.mp4
3.1 MB
Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-tUeaXXT2oDI.mp4
3.1 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/17. Check You Out-tgni8KzxWzA.mp4
3.1 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.mp4
3.1 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.mp4
3.1 MB
Part 09-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots-llvIDIu3Sw8.mp4
3.1 MB
Part 03-Module 01-Lesson 11_L4 Variability/18. Deviation from Mean-seTkSLAS43o.mp4
3.1 MB
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.mp4
3.1 MB
Part 17-Module 01-Lesson 14_Regression/04. Introduction to Linear Regression-RD4zbBvXDnM.mp4
3.1 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region-skeY26k1hSs.mp4
3.1 MB
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.mp4
3.1 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/34. Keyboards - SD of Differences--wbCbKqqaZY.mp4
3.1 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.mp4
3.1 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-QX_KFUXtHkw.mp4
3.1 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-QX_KFUXtHkw.mp4
3.1 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-Khxyqd5vtOo.mp4
3.1 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-dxw2VFq5sAc.mp4
3.1 MB
Part 17-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics-meNSO42JF6I.mp4
3.1 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/23. Marks And Filters-FeYRmZHHu0A.mp4
3.0 MB
Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-buxApBhZCO0.mp4
3.0 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.mp4
3.0 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/28. Rent - Find CI-1bXAy-6Pxf0.mp4
3.0 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2 Solution-ncqhpqt0Mik.mp4
3.0 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/13. SD of Sampling Distribution-rJ8NsbL5iTk.mp4
3.0 MB
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.mp4
3.0 MB
Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Ilu1JjjAbwA.mp4
3.0 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions-EvhIgrXtOao.mp4
3.0 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/06. 5 Number Summary to Variance-Ljhau0hrZ1g.mp4
3.0 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/13. Tracking Down the Remaining Problems-Xblj5rT9i0M.mp4
3.0 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/01. Instructors Introduction-lIvm8urf4GE.mp4
3.0 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-V7zAB9dUaFY.mp4
3.0 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/13. Pandas Series-V7zAB9dUaFY.mp4
3.0 MB
Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-CvB2qkSk1Zc.mp4
3.0 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/16. Comparing Row to Previous Row-Z_x5ZJyDZog.mp4
3.0 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma-NMnlSnu8DPI.mp4
3.0 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/14. Two-Tailed Critical Values 0.001-KD_AqWVG4Cc.mp4
3.0 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/35. Summary of the Update Function-IVmBlMgErzY.mp4
3.0 MB
Part 03-Module 01-Lesson 11_L4 Variability/20. Equation for Average Deviation-9jdZ9pfYP6A.mp4
3.0 MB
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-cUhgZ2BnWq0.mp4
3.0 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/01. Hypothesis Testing Introduction-Qi6F2rJAmrA.mp4
3.0 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/38. Keyboards - Cohen's d-yejk0jbkWBk.mp4
3.0 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/29. Let's Make a Bar Chart-PlhGAjAZFhw.mp4
3.0 MB
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.mp4
3.0 MB
Part 21-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.mp4
3.0 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/08. Calculating Correlation-yLql7kR_6GE.mp4
3.0 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/08. Calculating Correlation-yLql7kR_6GE.mp4
3.0 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/09. Gather Open Jupyter Notebook-IaExjsrVMgQ.mp4
3.0 MB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/06. Write the Conclusion-i3ozyhGPmIg.mp4
3.0 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.mp4
3.0 MB
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-0ZBp8oWySAc.mp4
3.0 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-pxaXkCjukGM.mp4
3.0 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/12. What Can You Create In Tableau-gNqIvf5iJA8.mp4
3.0 MB
Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-GTLvqNrAETc.mp4
3.0 MB
Part 11-Module 01-Lesson 09_Clustering/13. Some challenges of k-means-e2CdlG5P4WA.mp4
3.0 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/04. What is Data-ldTDAjrVsA8.mp4
3.0 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/25. Sorting the Data for Drawing Order-X-zVfcuacD4.mp4
3.0 MB
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.mp4
2.9 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Visual-PVbOzw5libM.mp4
2.9 MB
Part 12-Module 02-Lesson 05_Trees/02. Tree Basics-oaxLPzaXRDc.mp4
2.9 MB
Part 17-Module 01-Lesson 14_Regression/02. Introduction to Machine Learning-pLcFPPI1L-0.mp4
2.9 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.mp4
2.9 MB
Part 18-Module 02-Lesson 01_Gathering Data/08. Scraping Webpages -bAeGbBBAIkE.mp4
2.9 MB
Part 09-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width-TYN_LGAV3m8.mp4
2.9 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/14. Acne Medication - Decision-WzwHLFlkxVA.mp4
2.9 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/10. Interview Wrap-Up-sz4Ekcu9a_Q.mp4
2.9 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/07. Packages Overview-sCQoQsmI3F0.mp4
2.9 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-mIn7nMR092Q.mp4
2.9 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-mIn7nMR092Q.mp4
2.9 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.mp4
2.9 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/09. 06 Practice With Marks And Filters-RPAv7WLkutk.mp4
2.9 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example-Ae_UOATWmDM.mp4
2.9 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends-19ZQP5wzmKA.mp4
2.9 MB
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-R6oIvdBtsZw.mp4
2.9 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-q_zfkCwRg1w.mp4
2.9 MB
Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.mp4
2.9 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.mp4
2.9 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.mp4
2.9 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/01. Confidence Intervals Introduction-crleT4000ak.mp4
2.9 MB
Part 12-Module 02-Lesson 06_Graphs/04. Connectivity-4x6u2KtNDg4.mp4
2.9 MB
Part 05-Module 01-Lesson 05_Data Quality/20. Conclusion-fSwaNltHTio.mp4
2.9 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.mp4
2.9 MB
Part 03-Module 01-Lesson 11_L4 Variability/02. Should You Get an Account-pZ_GUg7z548.mp4
2.9 MB
Part 07-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects-OxL-gMTizUA.mp4
2.9 MB
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.mp4
2.9 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/33. Keyboards Point Estimate for Difference-Rw3QBEnIlJY.mp4
2.9 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/14. Andy - SDs Below-xE3Rgjv2Vww.mp4
2.9 MB
Part 03-Module 01-Lesson 11_L4 Variability/28. Avg. Squared Dev. in Words--_I23DcNTF0.mp4
2.9 MB
Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.mp4
2.9 MB
Part 09-Module 01-Lesson 02_R Basics/12. Factor Variables-0bkvt4KEqjE.mp4
2.9 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=-J9FWaCBXhIk.mp4
2.9 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=-J9FWaCBXhIk.mp4
2.9 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.mp4
2.9 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.mp4
2.9 MB
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-wJV1cRjmIYY.mp4
2.9 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/27. Communication-P36LwI-R2Vw.mp4
2.9 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Solution --faitcQ7SKs.mp4
2.9 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/10. Intro to Screen Scraping-RJyVIgUUemE.mp4
2.9 MB
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.mp4
2.9 MB
Part 18-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -BS_p9kwMEMk.mp4
2.9 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular-SCy8YH5xu3Q.mp4
2.9 MB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/21. Visualization design -TTGYKv5Qta0.mp4
2.9 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.mp4
2.9 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/08. Probability Mean or = 3-JSlSjQwhIAI.mp4
2.9 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/23. Rent - t-Critical Values-WTmFRvH2AmI.mp4
2.8 MB
Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-PlFG87qPSB4.mp4
2.8 MB
Part 13-Module 01-Lesson 05_Dimple.js/13. Adding an Axis with Dimple-7okDT6V9Mmk.mp4
2.8 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/43. Table Calculations-VJfCNO0J9jY.mp4
2.8 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/34. Keyboards - SD of Differences-Ej8yntoeBw0.mp4
2.8 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/31. Small Multiples And Dual Axis-bx6MxsoDqsI.mp4
2.8 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-AO8vSyAtfV4.mp4
2.8 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.mp4
2.8 MB
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.mp4
2.8 MB
Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-OzPNbN4L_L0.mp4
2.8 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/29. Rent - Margin of Error-q413Zzil8lQ.mp4
2.8 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/30. Sampling Distribution Shape-FJjI93XvC50.mp4
2.8 MB
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-7ZvLztG6xhg.mp4
2.8 MB
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-WxAWorS2SLg.mp4
2.8 MB
Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-K-rQ8KnmmH8.mp4
2.8 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.mp4
2.8 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/16. Pandas groupby()-w3D0no7E8uw.mp4
2.8 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/16. Pandas groupby()-w3D0no7E8uw.mp4
2.8 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/13. Visualizing Data-tqXBhXfWiDE.mp4
2.8 MB
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.mp4
2.8 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-VLgrNOLomc0.mp4
2.8 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-VLgrNOLomc0.mp4
2.8 MB
Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-TjY0Q66Yh-s.mp4
2.8 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.mp4
2.8 MB
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.mp4
2.8 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-CZnFt1rOfwc.mp4
2.8 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-Fkm7ogOussQ.mp4
2.8 MB
Part 13-Module 01-Lesson 05_Dimple.js/34. Summary of Dimple and Chart Types-OrdADko3k1Q.mp4
2.8 MB
Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-KFVdS328iC8.mp4
2.8 MB
Part 11-Module 01-Lesson 07_Regressions/25. Algorithms for Minimizing Squared Errors-Dw_9Dp6wcJ8.mp4
2.8 MB
Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-GUD6yl0A1Aw.mp4
2.8 MB
Part 03-Module 01-Lesson 11_L4 Variability/25. Squared Deviations-mVBWg3aPPhI.mp4
2.8 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/06. Connecting To Data-WmsAtqbwRI0.mp4
2.8 MB
Part 15-Module 01-Lesson 02_Design Principles/20. Onwards!-i-ulsdVHhCc.mp4
2.8 MB
Part 19-Module 01-Lesson 02_Design/22. Onwards!-i-ulsdVHhCc.mp4
2.8 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/02. Normalized Design Part One-LQq5F77ANiY.mp4
2.8 MB
Part 11-Module 01-Lesson 07_Regressions/32. Visualizing Regression-zQAHZhcsXoQ.mp4
2.8 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-aUc0FKD4834.mp4
2.8 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-zAQygY7v2Ds.mp4
2.8 MB
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.mp4
2.8 MB
Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-hS7cpq-sOeQ.mp4
2.8 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/18. Debugging Data Analysis Code -ReoDup994zk.mp4
2.8 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather CSV Files-FpWi4tExVwg.mp4
2.8 MB
Part 05-Module 02-Lesson 03_Elements of SQL/03. Types in the SQL World-8swA-PqlEP0.mp4
2.7 MB
Part 03-Module 01-Lesson 11_L4 Variability/19. Average Deviation-OCLlqMAbxBM.mp4
2.7 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/17. Type And Quality Plot - Part 2-Ui1rF6McOBA.mp4
2.7 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/16. Subquery Conclusion-TUYvx2K9-5k.mp4
2.7 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/40. Calculated Fields-tR-K9Mvd4B0.mp4
2.7 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-P1aYwQhPnPQ.mp4
2.7 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.mp4
2.7 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/03. 01 Connecting To Data-zuJPPSlbW2c.mp4
2.7 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/06. 04 Aggregation Granularity-GuOytlkqdrQ.mp4
2.7 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/11. In-Place vs. Not In-Place-TVyv8acRPrs.mp4
2.7 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place-TVyv8acRPrs.mp4
2.7 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/12. Two-Tailed Probability-68_OkDcn6dI.mp4
2.7 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/12. Ratio of SDs-E14J3Thd0lc.mp4
2.7 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.mp4
2.7 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/08. Self JOINs-tw_VzEGBOvI.mp4
2.7 MB
Part 11-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.mp4
2.7 MB
Part 13-Module 01-Lesson 07_Narrative Structures/44. Parsing Overview and Parsing Attendance-_tVC3JuW7to.mp4
2.7 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/02. Guinness-6V5K3VOGp8c.mp4
2.7 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/18. Conclusion-P7H8wjCIJ6k.mp4
2.7 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/19. Conclusion-P7H8wjCIJ6k.mp4
2.7 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/20. Shoes - 95 CI-Ld7EaNyua4c.mp4
2.7 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-611qWzIxGmU.mp4
2.7 MB
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-611qWzIxGmU.mp4
2.7 MB
Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables-08GsrEIOP9Q.mp4
2.7 MB
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.mp4
2.7 MB
Part 21-Module 01-Lesson 05_Scripting/05. Running A Python Script-vMKemwCderg.mp4
2.7 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/01. Welcome to Lesson 2-53b_nnGcnBY.mp4
2.7 MB
Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-HSeIrqW-YGw.mp4
2.7 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.mp4
2.7 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.mp4
2.7 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.mp4
2.7 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/12. Caution with Class Selections-fP30uBJljNk.mp4
2.7 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.mp4
2.7 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.mp4
2.7 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.mp4
2.7 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-BqQbAqok8JU.mp4
2.7 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-BqQbAqok8JU.mp4
2.7 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/02. Gambling in Vegas-qbcBbbm3lt8.mp4
2.7 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-HFCs3LbQ5Z0.mp4
2.7 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/24. Adjusting the Map Aesthetics-tc1Aai8e-w0.mp4
2.7 MB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/09. Extra Practice With Dashboards-Va2zNfnUC6o.mp4
2.6 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.mp4
2.6 MB
Part 12-Module 02-Lesson 05_Trees/16. Heapify-CAbDbiCfERY.mp4
2.6 MB
Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-udJvijJvs1M.mp4
2.6 MB
Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.mp4
2.6 MB
Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size-tl4mqs0SqX4.mp4
2.6 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.mp4
2.6 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region-SyNQ2mElRi0.mp4
2.6 MB
Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.mp4
2.6 MB
Part 03-Module 01-Lesson 11_L4 Variability/26. Sum of Squares-Vr3knoVJvlk.mp4
2.6 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.mp4
2.6 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-n7gp8USw0Jw.mp4
2.6 MB
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.mp4
2.6 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/16. Subqueries-YWZ-bgnZWaM.mp4
2.6 MB
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.mp4
2.6 MB
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.mp4
2.6 MB
Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-4EpW5acw55c.mp4
2.6 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/16. Using A Confidence Interval to Make A Decision-MghT95b6LbQ.mp4
2.6 MB
Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.mp4
2.6 MB
Part 13-Module 01-Lesson 07_Narrative Structures/32. From Dimple to D3-0yJzBWRQi5U.mp4
2.6 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-XUZIGbX3JIg.mp4
2.6 MB
Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-mpYpT6nZVEo.mp4
2.6 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 1-V7STsHoZ2gA.mp4
2.6 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/03. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.mp4
2.6 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/04. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.mp4
2.6 MB
Part 12-Module 02-Lesson 04_Maps and Hashing/02. Sets and Maps-gmIb-qZhTDQ.mp4
2.6 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value-6Z3BJWRuOAE.mp4
2.6 MB
Part 16-Module 03-Lesson 01_Basic SQL/18. ORDER BY Statement-wqj2As31LqI.mp4
2.6 MB
Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.mp4
2.6 MB
Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-GtR3dw2eq2w.mp4
2.6 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/11. Relationship Between SDs-8mHK1E3mR4E.mp4
2.6 MB
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.mp4
2.6 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution-oERHYF9QCkY.mp4
2.6 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/18. 08 Table Calculations-Vkf3Ft93zMc.mp4
2.6 MB
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-U3FUxkm1MxI.mp4
2.6 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/19. Outro-q7a9w02Uepw.mp4
2.6 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score-JdzOGxmq2jE.mp4
2.6 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.mp4
2.5 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/15. Conclusion-PXBdIBgFTL4.mp4
2.5 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/38. Something Fun-S3UsHyKkoww.mp4
2.5 MB
Part 13-Module 01-Lesson 05_Dimple.js/07. Javascript Debugger-AzbaV5CT9es.mp4
2.5 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/01. Introduction-2Y279421n3A.mp4
2.5 MB
Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-c1gvsNx_ypg.mp4
2.5 MB
Part 13-Module 01-Lesson 07_Narrative Structures/64. All World Cup Games Recap-tVtEEL5i_BE.mp4
2.5 MB
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-VERLCqDewrM.mp4
2.5 MB
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/01. Communicating with your data-KDnca1zszIo.mp4
2.5 MB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/01. Communicating With Your Data-KDnca1zszIo.mp4
2.5 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.mp4
2.5 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.mp4
2.5 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (Before Cleaning)-jJH3H8Rqv8s.mp4
2.5 MB
Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-Fi3uuGj8bhs.mp4
2.5 MB
Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ZlDdxWYv6jw.mp4
2.5 MB
Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-NRCs22HJ-vI.mp4
2.5 MB
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.mp4
2.5 MB
Part 03-Module 01-Lesson 11_L4 Variability/27. Average Squared Deviation-kmVqaJ6n9Vk.mp4
2.5 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.mp4
2.5 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/17. 07 Calculated Fields-dXEvq03E5lc.mp4
2.5 MB
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/08. Further Learning-SnLQlP5J7c8.mp4
2.5 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-pn3MunHovMc.mp4
2.5 MB
Part 19-Module 01-Lesson 02_Design/02. Lesson Overview-Gg77PqkQkhs.mp4
2.5 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion-xYqxZQmXCdI.mp4
2.5 MB
Part 16-Module 03-Lesson 01_Basic SQL/43. AND BETWEEN Operators-nBuDPneWcKY.mp4
2.5 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-AI9kNE00Los.mp4
2.5 MB
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.mp4
2.5 MB
Part 18-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate -CDRmFJHywp8.mp4
2.5 MB
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.mp4
2.5 MB
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.mp4
2.5 MB
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.mp4
2.5 MB
Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables-e8zSXnyskro.mp4
2.5 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/02. Accuracy Review-g3sxDtlGlAM.mp4
2.5 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/06. Subqueries Part II-jko-RrZd0R8.mp4
2.5 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.mp4
2.5 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.mp4
2.5 MB
Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-z2R5CqjXrkA.mp4
2.5 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-Vx9bxJHQJf8.mp4
2.4 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-Vx9bxJHQJf8.mp4
2.4 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely-9jGIDxEr9A4.mp4
2.4 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/28. Improving Plots and Sharing Findings-anglRHbmsfw.mp4
2.4 MB
Part 13-Module 01-Lesson 07_Narrative Structures/49. Orienting and Drawing the Axes-I9-ysMlq-Xc.mp4
2.4 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-7umkXt9U5lE.mp4
2.4 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-7umkXt9U5lE.mp4
2.4 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/34. Prone to Misinterpretations-DUVB_GCcado.mp4
2.4 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-KuihzV_LLAE.mp4
2.4 MB
Part 12-Module 02-Lesson 05_Trees/08. Search and Delete-KbL-HK3ztX8.mp4
2.4 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/09. Experiment II-fq4eO7CybA4.mp4
2.4 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-e_8DmUBHAao.mp4
2.4 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/39. Keyboards - CI for Dependent Samples-POKBAWQ2S7U.mp4
2.4 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic-A8xSEFaFuBc.mp4
2.4 MB
Part 11-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.mp4
2.4 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/05. Mean of Each Sample-n7II63ei3LU.mp4
2.4 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Aliases for Multiple Window Functions-RWe03bULYnM.mp4
2.4 MB
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-f_SBhjbfmPw.mp4
2.4 MB
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.mp4
2.4 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/23. Critical Values 0.05-KQZnIM7YWAg.mp4
2.4 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.mp4
2.4 MB
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.mp4
2.4 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/09. One-Tailed t-Test-3rL-Vk-QIB8.mp4
2.4 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-9bsmO7cKzPk.mp4
2.4 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/07. Significance-f0ZWCaOKW1Q.mp4
2.4 MB
Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-F7PIJM0q524.mp4
2.4 MB
Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.mp4
2.4 MB
Part 11-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.mp4
2.4 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 2-CyeB16-eGSg.mp4
2.4 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/21. Adding SVG Elements-Vx9n2qXwL6w.mp4
2.4 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-_Z4d6-d-glM.mp4
2.4 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-_Z4d6-d-glM.mp4
2.4 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/23. L3 outro-y46uDftUXHo.mp4
2.4 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/47. What's Next-y46uDftUXHo.mp4
2.4 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/02. Technical Interlude-QWA06Ro4ix0.mp4
2.4 MB
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.mp4
2.4 MB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/14. COALESCE-86vgu-ECBCQ.mp4
2.4 MB
Part 07-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2-It6AEuSDQw0.mp4
2.4 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/03. Meal Prices-f_WdPsfeLDs.mp4
2.4 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-ObSZnD336CA.mp4
2.4 MB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/09. L4_Mini Project-CGPO68cOCgc.mp4
2.4 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/14. Analyzing Multiple Metrics-DtZghKNa7Ak.mp4
2.4 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/09. Renaming Columns-3Oo4gUP2_Rw.mp4
2.4 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip Solution -Pzy8nHA_EJc.mp4
2.4 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size-_Oh9-SQDtYg.mp4
2.4 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.mp4
2.3 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.mp4
2.3 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Window Functions Conclusion-2ZdocDMw7D8.mp4
2.3 MB
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.mp4
2.3 MB
Part 09-Module 01-Lesson 03_Explore One Variable/06. Estimating Your Audience Size-FfzVPWM5DZ8.mp4
2.3 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-MPPgcjHAfkA.mp4
2.3 MB
Part 05-Module 02-Lesson 01_Data and Tables/08. Aggregations-TE9uvPwvpu4.mp4
2.3 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-1GuHNqJNY2M.mp4
2.3 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/26. t-Statistic-P4tyKSWJUZc.mp4
2.3 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/09. Data Types Summary-T-KrQoAJUpI.mp4
2.3 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error-ZU9uRiqLgxA.mp4
2.3 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01-6RNfHbEL4ZQ.mp4
2.3 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/01. Intro to the PDF-QTVWqk09q1A.mp4
2.3 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/05. Confidence Interval for a Difference In Means-8hrWGzjyhck.mp4
2.3 MB
Part 03-Module 01-Lesson 11_L4 Variability/18. Deviation from Mean-M43NnIroHws.mp4
2.3 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-m2waMNsE1sU.mp4
2.3 MB
Part 03-Module 01-Lesson 20_L8 Estimation/12. Generalize CI-HgumODgJSdQ.mp4
2.3 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-si8AcC5pTfM.mp4
2.3 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-si8AcC5pTfM.mp4
2.3 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/03. What Is Coming Up-oDJsnQcCPr4.mp4
2.3 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.mp4
2.3 MB
Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.mp4
2.3 MB
Part 13-Module 01-Lesson 07_Narrative Structures/40. Creating Time and Attendance Scales-PgAp8ob4hIM.mp4
2.3 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/12. What's a DB-API-06LsRU4pmkA.mp4
2.3 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/13. Manipulating DOM Nodes-RMUHrUa7HR0.mp4
2.3 MB
Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.mp4
2.3 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely-oIFRsiD2mQE.mp4
2.3 MB
Part 16-Module 03-Lesson 01_Basic SQL/34. LIKE Operator-O5z6eWkNip4.mp4
2.3 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-LHLgEooUT4E.mp4
2.3 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis-Pk_BMZINZ0k.mp4
2.3 MB
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.mp4
2.3 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-j2SP83afRS0.mp4
2.3 MB
Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.mp4
2.3 MB
Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.mp4
2.3 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.mp4
2.3 MB
Part 13-Module 01-Lesson 05_Dimple.js/10. Dimple Axes, Series and Fields-nSqsoDChbEU.mp4
2.3 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-47JDwoDUxP8.mp4
2.3 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/22. Having-D4gmN0vnk58.mp4
2.3 MB
Part 17-Module 01-Lesson 14_Regression/01. Regression Introduction-PKqSS0TzXeA.mp4
2.3 MB
Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-B_fHrMIzIgE.mp4
2.3 MB
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.mp4
2.3 MB
Part 18-Module 02-Lesson 01_Gathering Data/17. JSON Files In Python-8JdUknZP59Q.mp4
2.2 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/18. Conclusion-qmGjRpMVBz8.mp4
2.2 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/16. Mean Number of Shoes-DtdsK8K1OtI.mp4
2.2 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-q46nO0mznXM.mp4
2.2 MB
Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-dXS9vjgXyg4.mp4
2.2 MB
Part 12-Module 02-Lesson 04_Maps and Hashing/08. Hash Maps-A-ahUVi8pYQ.mp4
2.2 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/01. Case Study Introduction-J5uvdPxHIfs.mp4
2.2 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.mp4
2.2 MB
Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-I_v6ueT0k3M.mp4
2.2 MB
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.mp4
2.2 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210-OBxWYhF4VdI.mp4
2.2 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/03. Data Types and NULLs-RgTcYwKqtYI.mp4
2.2 MB
Part 16-Module 03-Lesson 02_SQL Joins/03. Your First JOIN-HkX9fkNRbU8.mp4
2.2 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-8HFOaRdDpek.mp4
2.2 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-8HFOaRdDpek.mp4
2.2 MB
Part 16-Module 03-Lesson 01_Basic SQL/27. WHERE with Non-Numeric Data-_pLx7MHOyjo.mp4
2.2 MB
Part 09-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.mp4
2.2 MB
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.mp4
2.2 MB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/17. Data Cleaning Conclusion-KkHqnvD9BWY.mp4
2.2 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error-_h2C0TCvXvA.mp4
2.2 MB
Part 17-Module 01-Lesson 14_Regression/15. Fitting A Regression Line In Python-0CiMDbEUeS4.mp4
2.2 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-P8ZxaAQTZXQ.mp4
2.2 MB
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-PYNWtLgtRfU.mp4
2.2 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/12. Using the Z-Table-EeT7osOfzJE.mp4
2.2 MB
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.mp4
2.2 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/01. Compare Sample Means-l9Sy4qoLHVo.mp4
2.2 MB
Part 09-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.mp4
2.2 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction-FGbxq1hQgtk.mp4
2.2 MB
Part 13-Module 01-Lesson 04_Design Principles/32. Do No Harm-BIQPOMfDXjs.mp4
2.2 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/17. Finches - Mean and s-XhVy8ALgO0U.mp4
2.2 MB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.mp4
2.2 MB
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.mp4
2.2 MB
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.mp4
2.2 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-YY31Ggi4XyQ.mp4
2.2 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/34. Does Low Probability = Causation-KaBa9N2TdnQ.mp4
2.2 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/04. Gathering Data-r7BHGq_0P9Q.mp4
2.2 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Data Types-gT6EYlsLZkE.mp4
2.2 MB
Part 05-Module 02-Lesson 03_Elements of SQL/07. The One Thing SQL is Terrible At-wrjCB1abNyM.mp4
2.2 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/05. CREATE TABLE and Types-7DCw86WMpYo.mp4
2.2 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.mp4
2.2 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.mp4
2.2 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.mp4
2.2 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/20. Standard Error When n Increases-mbCavcKeZqo.mp4
2.2 MB
Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR-sl51Cpwy5RA.mp4
2.2 MB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/02. Shortest Path Problem-huKUM97Vve8.mp4
2.2 MB
Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-n1EbdV_CTcc.mp4
2.2 MB
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.mp4
2.2 MB
Part 17-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.mp4
2.2 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/05. COUNT NULLs-ngxgqfFFFLQ.mp4
2.1 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/02. Action Time-80DSWU8ZUoQ.mp4
2.1 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/29. Klout Sampling Distribution (SD)-Qlg5L4TWcZs.mp4
2.1 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/20. Alternative Hypothesis-EH59aCNpHS8.mp4
2.1 MB
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.mp4
2.1 MB
Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy-m989etSymQQ.mp4
2.1 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-LCrrPfsXaVc.mp4
2.1 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-Lb_v4vj3TNs.mp4
2.1 MB
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-Lb_v4vj3TNs.mp4
2.1 MB
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.mp4
2.1 MB
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-uHIZl6MCiPY.mp4
2.1 MB
Part 16-Module 03-Lesson 01_Basic SQL/06. Why Businesses Choose Databases-j4ey7--h9r8.mp4
2.1 MB
Part 18-Module 02-Lesson 01_Gathering Data/22. Why Businesses Choose Databases-j4ey7--h9r8.mp4
2.1 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/35. Keyboards - t-Statistic-aE-ZZw8QVWo.mp4
2.1 MB
Part 13-Module 01-Lesson 07_Narrative Structures/20. The Martini Glass-h8b8SOsSiT4.mp4
2.1 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/13. Katie - SDs Below-oV8f7eO_1hA.mp4
2.1 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-El5cY2jlzuM.mp4
2.1 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/17. Evidence to Reject the Null-a5RRRMRZl8I.mp4
2.1 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample-I487nBkmUoM.mp4
2.1 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/18. Better Sample-I487nBkmUoM.mp4
2.1 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM-jHzmtwd-xTs.mp4
2.1 MB
Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.mp4
2.1 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price-m9IQqYf6ThU.mp4
2.1 MB
Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-jKZAcZw9xLA.mp4
2.1 MB
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-O5B-Z5SUoc8.mp4
2.1 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.mp4
2.1 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic-y1QSAIUlupg.mp4
2.1 MB
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-qhhrjvLF8H8.mp4
2.1 MB
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-xSQTzAeeoEc.mp4
2.1 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/16. Roll 2 Dice-D4bQbaCAUoE.mp4
2.1 MB
Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-49B5hlxzTRc.mp4
2.1 MB
Part 11-Module 01-Lesson 03_SVM/13. Nonlinear SVMs-6UgInp_gf1w.mp4
2.1 MB
Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance-QReeBef_7vM.mp4
2.1 MB
Part 13-Module 01-Lesson 05_Dimple.js/05. A Simple HTTP Server-h8Fa24E_I5s.mp4
2.1 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/30. Filtering-vXGDYzAo22Y.mp4
2.1 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/03. Assessing the Quality of Data Pt. 1-Dezhyk312lQ.mp4
2.1 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-VkZ-W3kh9PA.mp4
2.1 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.mp4
2.1 MB
Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.mp4
2.1 MB
Part 03-Module 01-Lesson 11_L4 Variability/01. Social Networkers' Salaries-4nYdxMABeBc.mp4
2.0 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/19. Null Hypothesis-ldiOcCeZvx4.mp4
2.0 MB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Operator-3vLGEuXAAvA.mp4
2.0 MB
Part 18-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 2-9YPOlROXNZM.mp4
2.0 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-b7oUjvNJWCc.mp4
2.0 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/21. t-Critical-9-yTPJl_DIw.mp4
2.0 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.mp4
2.0 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/19. Between 10 and 16-lMm_BrpheLM.mp4
2.0 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-80BAbiEWsaY.mp4
2.0 MB
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.mp4
2.0 MB
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.mp4
2.0 MB
Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means-kuTOS0wZJd4.mp4
2.0 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -Vf-EK6vg6Uc.mp4
2.0 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/09. Maps in D3-DAfs_MCYP0o.mp4
2.0 MB
Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.mp4
2.0 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-_zx9cahSRNE.mp4
2.0 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-m8d9J5w3axY.mp4
2.0 MB
Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Using With-OQ-Y0mMjm00.mp4
2.0 MB
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.mp4
2.0 MB
Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/01. 7. Ode to n-c2Das5kJFe4.mp4
2.0 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.mp4
2.0 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.mp4
2.0 MB
Part 16-Module 03-Lesson 01_Basic SQL/40. NOT Operator-dSQF87oW8a0.mp4
2.0 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.mp4
2.0 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/44. Adding Events to Buttons-UXRemP4hIyw.mp4
2.0 MB
Part 03-Module 01-Lesson 11_L4 Variability/36. Find Values-JP-mQPN9Sl4.mp4
2.0 MB
Part 13-Module 01-Lesson 07_Narrative Structures/58. Juxtaposition and Comparison-abaD-wvlbkg.mp4
2.0 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.mp4
2.0 MB
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.mp4
2.0 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/17. Finches - Mean and s-nInJKeAmAeY.mp4
2.0 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-6pxpT3bZI54.mp4
2.0 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.mp4
2.0 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/32. Enter Update Exit-lmDLMOPOj5I.mp4
2.0 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-Jbqf8OBORDg.mp4
2.0 MB
Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-Jbqf8OBORDg.mp4
2.0 MB
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-IC47yHGmgMk.mp4
2.0 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/07. Loading Data into a DataFrame-N66_j0gxuhg.mp4
2.0 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/07. Loading Data into a DataFrame-N66_j0gxuhg.mp4
2.0 MB
Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-JsFlZfNpVl4.mp4
2.0 MB
Part 09-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.mp4
2.0 MB
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-9DHPaCjg9HM.mp4
2.0 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis-kW_p0VHNEPM.mp4
2.0 MB
Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-rexAHoCGFMs.mp4
2.0 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.mp4
1.9 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means-TpsMv7isR6U.mp4
1.9 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.mp4
1.9 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/19. Standard Error for Avg of 5 Dice-18DMT9dnLPE.mp4
1.9 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess-mCZxHNB1u4w.mp4
1.9 MB
Part 13-Module 01-Lesson 04_Design Principles/23. Careful with Color-aKwXLGs0Rfs.mp4
1.9 MB
Part 09-Module 01-Lesson 02_R Basics/15. Data Munging-q_Ghc6VsDo0.mp4
1.9 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.mp4
1.9 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.mp4
1.9 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Subqueries Using WITH-IszTmDKyKHI.mp4
1.9 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price-Ck4i1Yk4pT0.mp4
1.9 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/01. 26 Spread Part 1-zb76Z_viYLY.mp4
1.9 MB
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-3FO2y4tlZ3A.mp4
1.9 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 3-oVGmi4zBOT8.mp4
1.9 MB
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.mp4
1.9 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/15. Getting Data from First Week -iT1vtUy2utg.mp4
1.9 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment-zWmH6ajoLtE.mp4
1.9 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-_c_chcNiHyo.mp4
1.9 MB
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.mp4
1.9 MB
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.mp4
1.9 MB
Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.mp4
1.9 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.mp4
1.9 MB
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.mp4
1.9 MB
Part 18-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 -Ngl_TsqhMsc.mp4
1.9 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.mp4
1.9 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means-7iOMOs56gZE.mp4
1.9 MB
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.mp4
1.9 MB
Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete--uRSI_oybJQ.mp4
1.9 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/02. Data Overview-V-iPdJfrscQ.mp4
1.9 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.mp4
1.9 MB
Part 03-Module 01-Lesson 11_L4 Variability/31. Calculate SD-E1iDHrumLoo.mp4
1.9 MB
Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-vxS-Kh4eI0U.mp4
1.9 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/33. What Happened-6mxt0l8IpOM.mp4
1.8 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values--xVYQQHNNuM.mp4
1.8 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values--xVYQQHNNuM.mp4
1.8 MB
Part 16-Module 03-Lesson 01_Basic SQL/37. IN Operator-_JPO7wwX3uA.mp4
1.8 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic-LDdm06-FHYI.mp4
1.8 MB
Part 11-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!-UjaFiRdHPZg.mp4
1.8 MB
Part 13-Module 01-Lesson 05_Dimple.js/33. Advantages with CSS-lCTey7ryZ1A.mp4
1.8 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/04. DF - Choose n Numbers-4XEJJC-vSRw.mp4
1.8 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/15. Standardizing Each Column Again-7NofF-s1UGY.mp4
1.8 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/15. Standardizing Each Column Again-7NofF-s1UGY.mp4
1.8 MB
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-8vi9b_LHHz8.mp4
1.8 MB
Part 12-Module 02-Lesson 05_Trees/13. BST Complications-pcB0wV7myy4.mp4
1.8 MB
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.mp4
1.8 MB
Part 03-Module 01-Lesson 11_L4 Variability/25. Squared Deviations-oA37LlWNYCw.mp4
1.8 MB
Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.mp4
1.8 MB
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.mp4
1.8 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/07. Categorical Ordinal Nominal Data-k5bLaPGY2Vw.mp4
1.8 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.mp4
1.8 MB
Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR-o2n0nea_1T0.mp4
1.8 MB
Part 13-Module 01-Lesson 07_Narrative Structures/60. Context for the Reader-_GkNEO9qeWI.mp4
1.8 MB
Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-0X7voyhbZ8k.mp4
1.8 MB
Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.mp4
1.8 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5-HbS35vDe_x0.mp4
1.8 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-9bNGgRojUC0.mp4
1.8 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/27. Klout Parameters-CLGwm6tBHlk.mp4
1.8 MB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Statement-DRmkKVhe6-s.mp4
1.8 MB
Part 03-Module 01-Lesson 11_L4 Variability/22. Absolute Deviations-baWB4xYNMIs.mp4
1.8 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/02. Probability-Wf7m7ygRvz8.mp4
1.8 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.mp4
1.8 MB
Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-FY9_6rOPk6c.mp4
1.8 MB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/12. Congratulations!-sCQ7ZViODaw.mp4
1.8 MB
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.mp4
1.8 MB
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.mp4
1.8 MB
Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-ygveMIhCtDg.mp4
1.8 MB
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.mp4
1.8 MB
Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.mp4
1.8 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-8oM8KjsntG8.mp4
1.8 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.mp4
1.8 MB
Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-095MTpItufM.mp4
1.8 MB
Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.mp4
1.8 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-LoLj_Ecohew.mp4
1.7 MB
Part 03-Module 01-Lesson 11_L4 Variability/27. Average Squared Deviation-xW3JXTmUlEE.mp4
1.7 MB
Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250-mCp7zkPv6o4.mp4
1.7 MB
Part 17-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.mp4
1.7 MB
Part 16-Module 03-Lesson 01_Basic SQL/30. Arithmetic Operators-fgcJdiNECxI.mp4
1.7 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/29. Cohen's d-smedG3-3mOE.mp4
1.7 MB
Part 18-Module 03-Lesson 01_Assessing Data/20. You Can Iterate-ZU8EnPbR-pk.mp4
1.7 MB
Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-3nZ2FL7C3sU.mp4
1.7 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/28. Show Me-Jpk99mgmwaA.mp4
1.7 MB
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.mp4
1.7 MB
Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-8IzQG_2WAcs.mp4
1.7 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post-p-ma7uqFNCM.mp4
1.7 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values-CRlOfleyRNY.mp4
1.7 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.mp4
1.7 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic-AeByX89sS4g.mp4
1.7 MB
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-v2_aFAmQxfw.mp4
1.7 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-2wHoLFHnPZs.mp4
1.7 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.mp4
1.7 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision-fgg81QJg89s.mp4
1.7 MB
Part 17-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.mp4
1.7 MB
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.mp4
1.7 MB
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-lS5DfbsWH34.mp4
1.7 MB
Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-pq31lSXEQl0.mp4
1.7 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference-eTNZnE_O_RM.mp4
1.7 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-o_qyeIeRb_Y.mp4
1.7 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.mp4
1.7 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.mp4
1.7 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/25. Transition to Tech Portion-WovqufP4nk0.mp4
1.7 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.mp4
1.7 MB
Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-ncFtwW5urHk.mp4
1.7 MB
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-cuBxHYSPrkA.mp4
1.7 MB
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-uETh8McUAfY.mp4
1.7 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/27. Statistically Significant-VXgMxs0tiBw.mp4
1.7 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/14. Anscombe’s Quartet-Ftp3mmItV-k.mp4
1.7 MB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Anscombe’s Quartet-Ftp3mmItV-k.mp4
1.7 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.mp4
1.7 MB
Part 13-Module 01-Lesson 05_Dimple.js/14. Adding a Series with Dimple-clyCsNwceP0.mp4
1.7 MB
Part 03-Module 01-Lesson 20_L8 Estimation/11. Generalize Point Estimate-JveZxEnq9bI.mp4
1.7 MB
Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.mp4
1.7 MB
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-8Ygq5dRV0Kk.mp4
1.7 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/13. Two-Tailed Critical Values 0.01-Kb_OuJuCFH0.mp4
1.7 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-gww_oBZTf5k.mp4
1.7 MB
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.mp4
1.7 MB
Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-VkQwfVQ00EQ.mp4
1.7 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.mp4
1.6 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.mp4
1.6 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.mp4
1.6 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.mp4
1.6 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error-cLyzI4feDEw.mp4
1.6 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis-u6vw-FcHT-M.mp4
1.6 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-nRurXCTYxG4.mp4
1.6 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/13. Line Plots-GsaBT47pjgQ.mp4
1.6 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/31. Raining-UNASgS676Hc.mp4
1.6 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200--scGDVG9KJ8.mp4
1.6 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/30. CASE Statements and Aggregations-asSXB6iD3z4.mp4
1.6 MB
Part 13-Module 01-Lesson 07_Narrative Structures/34. Updated World Cup Data Set-tA_je-rSL7c.mp4
1.6 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate-eu1gO_76pSY.mp4
1.6 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular-W5qXCZ-nrHM.mp4
1.6 MB
Part 13-Module 01-Lesson 04_Design Principles/02. Visual Encodings Recap-zyroaZ34ltA.mp4
1.6 MB
Part 13-Module 01-Lesson 05_Dimple.js/25. Bar Chart Issues-MNsMZH1Y0Js.mp4
1.6 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-9frwavCQvGg.mp4
1.6 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference-yu70KwoztEg.mp4
1.6 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/12. DataFrame apply()-aGEUhSRys8w.mp4
1.6 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/12. DataFrame apply()-aGEUhSRys8w.mp4
1.6 MB
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-5v1jxDIwGqk.mp4
1.6 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price-mlNMENDGqtk.mp4
1.6 MB
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.mp4
1.6 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/33. Probability of Obtaining Mean-wQ3iwH9b10w.mp4
1.6 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/31. Good Job!-ZZoeeLpWcmU.mp4
1.6 MB
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.mp4
1.6 MB
Part 03-Module 01-Lesson 11_L4 Variability/24. Formula for Avg. Abs. Dev.-_c780DW5Wuw.mp4
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.mp4
1.6 MB
Part 03-Module 01-Lesson 11_L4 Variability/38. Bessel's Correction-fghrG_GXWhw.mp4
1.6 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/01. Lesson Overview-DkjRzNwjSfo.mp4
1.6 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-r2s9INGd-Ls.mp4
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Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-FpQm_dYA9LM.mp4
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Part 11-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.mp4
1.6 MB
Part 03-Module 01-Lesson 20_L8 Estimation/02. Mean of Treated Population-jC4--44m3-I.mp4
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Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-0PFq8zoaNWU.mp4
1.6 MB
Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-0PFq8zoaNWU.mp4
1.6 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/23. Pooled Variance Sum of Squares-c0lWwW1Z9Ac.mp4
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/30. Sampling Distribution Shape-UMEckGyua6o.mp4
1.6 MB
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line-O4jFvJWal6s.mp4
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Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.mp4
1.6 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.mp4
1.6 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.mp4
1.6 MB
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.mp4
1.6 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-ZO7y9tsSQ0A.mp4
1.6 MB
Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-vfEi3aOawTI.mp4
1.6 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM-4FAowd-l1p4.mp4
1.6 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1 Solution -Noykh9Zt6aI.mp4
1.6 MB
Part 03-Module 01-Lesson 11_L4 Variability/06. Mark Z the Outlier-_UyoOnmH1X8.mp4
1.5 MB
Part 13-Module 01-Lesson 05_Dimple.js/27. Bar Chart The Bad-FCapLzYUQSo.mp4
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review-xzZZZCZk5YM.mp4
1.5 MB
Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-9AVeGkUcPYQ.mp4
1.5 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200-Ss00WF8qXHk.mp4
1.5 MB
Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean-dsje3j3gn_s.mp4
1.5 MB
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.mp4
1.5 MB
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-pt_S3HwE5GY.mp4
1.5 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI-S8sB8ph_bQM.mp4
1.5 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/04. Total Number of Samples-s0J73PTr9Rw.mp4
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Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-WDADret_QqE.mp4
1.5 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/21. Visualize P-Value-GHw4SRGYd5Y.mp4
1.5 MB
Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-R0RqC-yerD4.mp4
1.5 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.mp4
1.5 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/19. Lessons Completed in First Week -kL0HS6KWRcw.mp4
1.5 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/img/set-up-reminder.gif
1.5 MB
Part 09-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.mp4
1.5 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/20. SD of Standardized Distribution-0JZyJ5_T858.mp4
1.5 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/16. Pandas Series apply()-lhcl1UjM_0Q.mp4
1.5 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/17. Pandas Series apply()-lhcl1UjM_0Q.mp4
1.5 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic-kJxLPlQC-lQ.mp4
1.5 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/22. SEM-gl4ogBY9AOI.mp4
1.5 MB
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-2FQu07aKLwg.mp4
1.5 MB
Part 13-Module 01-Lesson 05_Dimple.js/19. Adding the Series and Drawing the Chart-2zcZXJzW0aw.mp4
1.5 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-b1V_L3qFIUk.mp4
1.5 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/07. Sampling Distribution-kQevFvu_dL0.mp4
1.5 MB
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.mp4
1.5 MB
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.mp4
1.5 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test--Ecdsb39FnM.mp4
1.5 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/12. Two-Tailed Probability-KwbK0InYgvE.mp4
1.5 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Percentiles-Qro8uvysnys.mp4
1.5 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/17. Plotting in Pandas-ujJShz9YfAU.mp4
1.5 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/18. Plotting in Pandas-ujJShz9YfAU.mp4
1.5 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-U74HWk-E_jg.mp4
1.5 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less-1PkuYCWwc_g.mp4
1.5 MB
Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-l7P-e1M_qPA.mp4
1.5 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/25. NEW Create a Radius Scale-fdylxSVOsnw.mp4
1.5 MB
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-Xrl2Hd--NWs.mp4
1.5 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-Z5nOpgKYYj4.mp4
1.5 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.mp4
1.5 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-UnkrtPPx9-c.mp4
1.5 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning-XDfqzA6nkqk.mp4
1.5 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-a6oG3g7aKR4.mp4
1.5 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-a6oG3g7aKR4.mp4
1.5 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/15. Finches-Y6qz1XqyO9w.mp4
1.5 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/17. Performance Tuning 3-hIAE8W6x5O8.mp4
1.5 MB
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-Njbmexuo7fo.mp4
1.5 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel-yg5c1caIB4E.mp4
1.5 MB
Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.mp4
1.5 MB
Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.mp4
1.4 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning-DKxww0fCCAA.mp4
1.4 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 1-APRpwqFpGwI.mp4
1.4 MB
Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings--laXTx9corQ.mp4
1.4 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean-Hj2HADsZ-rM.mp4
1.4 MB
Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio-R2a1wC3k0JM.mp4
1.4 MB
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.mp4
1.4 MB
Part 03-Module 01-Lesson 11_L4 Variability/01. Social Networkers' Salaries-jNUbORceQPA.mp4
1.4 MB
Part 13-Module 01-Lesson 07_Narrative Structures/37. Visualize Every Game of the World Cup-fxgnL-Lv684.mp4
1.4 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size-tX7p7HXlKBQ.mp4
1.4 MB
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.mp4
1.4 MB
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-FY0DXe0lfrI.mp4
1.4 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.mp4
1.4 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.mp4
1.4 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-QeTWVPi1Evo.mp4
1.4 MB
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-jJSkp9n3kA8.mp4
1.4 MB
Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.mp4
1.4 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/17. Evidence to Reject the Null-BHRLT1tJXHU.mp4
1.4 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.mp4
1.4 MB
Part 17-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.mp4
1.4 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-dSgIDN1gz5k.mp4
1.4 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/47. Start Creating-Nr1w-Hxjld4.mp4
1.4 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price-MZyle39D5Ks.mp4
1.4 MB
Part 13-Module 01-Lesson 05_Dimple.js/15. The Benefits of Dimple-PkCeV9KNiMg.mp4
1.4 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less-wDRJK3htUZE.mp4
1.4 MB
Part 16-Module 03-Lesson 01_Basic SQL/03. Entity Relationship Diagrams-YY2TAJLEINA.mp4
1.4 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/16. GROUP BY Part II-0HQ-TshNNQA.mp4
1.4 MB
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.mp4
1.4 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/37. Probability of Mean-dB5wr3taV7Y.mp4
1.4 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-QWWq77k-K_0.mp4
1.4 MB
Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-QWWq77k-K_0.mp4
1.4 MB
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-Bp6oBbLw8qE.mp4
1.4 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262-ulXPRo2lgC8.mp4
1.4 MB
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.mp4
1.4 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/04. More Examples-gj-or8b8TmM.mp4
1.4 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/04. COUNT-b4FCWAEGmLg.mp4
1.4 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test-AXYl4jWsA3o.mp4
1.3 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/21. Conclusion-UFwgr6tLcuI.mp4
1.3 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/37. Keyboards - Decision-PXDcczTlqLc.mp4
1.3 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.mp4
1.3 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-P1NzBPnfl2E.mp4
1.3 MB
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.mp4
1.3 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/33. Highlight Countries-wjUenfTcSG0.mp4
1.3 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/03. What is the Difference-I3tQvrCgNrQ.mp4
1.3 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.mp4
1.3 MB
Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.mp4
1.3 MB
Part 05-Module 02-Lesson 03_Elements of SQL/08. The Experiment Page--GlHaeB-vic.mp4
1.3 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/16. -6-NsyLPx738.mp4
1.3 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-Vp43h6ZRyoQ.mp4
1.3 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-Vp43h6ZRyoQ.mp4
1.3 MB
Part 16-Module 03-Lesson 02_SQL Joins/10. ALIAS-viWHJaxWTvw.mp4
1.3 MB
Part 16-Module 03-Lesson 01_Basic SQL/07. How Databases Store Data-H0C9z_sRvLE.mp4
1.3 MB
Part 18-Module 02-Lesson 01_Gathering Data/22. How Databases Store Data-H0C9z_sRvLE.mp4
1.3 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2-ZEkbLbmfHvg.mp4
1.3 MB
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.mp4
1.3 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/06. CREATE and DROP databases-3kycKkbQK6A.mp4
1.3 MB
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.mp4
1.3 MB
Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-Bb2K_pql26Y.mp4
1.3 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/35. Keyboards - t-Statistic-JwrCtWoPBjo.mp4
1.3 MB
Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-BbJfVyCm21o.mp4
1.3 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-n7v-y8UrVJ0.mp4
1.3 MB
Part 11-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.mp4
1.3 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/36. Keyboards - t-Critical Values-AP3YFEoi8_M.mp4
1.3 MB
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.mp4
1.3 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean-p3e965clFyU.mp4
1.3 MB
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-bnwLadF8gKo.mp4
1.3 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value-5pnYBObhGJk.mp4
1.3 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.mp4
1.3 MB
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.mp4
1.3 MB
Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-5dt0N4XN-y4.mp4
1.3 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data-AJF5smH1TJU.mp4
1.3 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.mp4
1.3 MB
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.mp4
1.3 MB
Part 03-Module 01-Lesson 11_L4 Variability/22. Absolute Deviations-pFyPTDVN41Q.mp4
1.3 MB
Part 07-Module 01-Lesson 01_GitHub Review/img/screen-shot-2017-10-31-at-1.06.42-pm.png
1.3 MB
Part 08-Module 01-Lesson 01_Conduct a Job Search/img/screen-shot-2017-10-31-at-1.06.42-pm.png
1.3 MB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/img/screen-shot-2017-10-31-at-1.06.42-pm.png
1.3 MB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/img/screen-shot-2017-10-31-at-1.06.42-pm.png
1.3 MB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/img/screen-shot-2017-10-31-at-1.06.42-pm.png
1.3 MB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/img/screen-shot-2017-10-31-at-1.06.42-pm.png
1.3 MB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/img/screen-shot-2017-10-31-at-1.06.42-pm.png
1.3 MB
Part 10-Module 01-Lesson 02_LinkedIn Review/img/screen-shot-2017-10-31-at-1.06.42-pm.png
1.3 MB
Part 10-Module 01-Lesson 03_Udacity Professional Profile/img/screen-shot-2017-10-31-at-1.06.42-pm.png
1.3 MB
Part 12-Module 01-Lesson 05_Interview Practice/img/screen-shot-2017-10-31-at-1.06.42-pm.png
1.3 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/img/screen-shot-2017-10-31-at-1.06.42-pm.png
1.3 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/04. 02 Joining Tables-vSjKBMgW1Fw.mp4
1.3 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-aW9OOZKfqR8.mp4
1.3 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/09. Combining Data-7KICenO-lKc.mp4
1.3 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/img/760018543.gif
1.2 MB
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.mp4
1.2 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma-VMkt5knD4VU.mp4
1.2 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom-GOwsOqdMY8w.mp4
1.2 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions--xSSuPcrrA8.mp4
1.2 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/23. Convert to Z-Score-tBlCLuL2tFc.mp4
1.2 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/16. Finches - n and DF-DvpOpY9ScQ0.mp4
1.2 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.mp4
1.2 MB
Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.mp4
1.2 MB
Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-QfIgUDXPhi8.mp4
1.2 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-HAQ0-Skvzmc.mp4
1.2 MB
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-HAQ0-Skvzmc.mp4
1.2 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-FwaYsmnlLM4.mp4
1.2 MB
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-FwaYsmnlLM4.mp4
1.2 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-4Ywln5AT6Hc.mp4
1.2 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.mp4
1.2 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.mp4
1.2 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-93y6ms_fuQQ.mp4
1.2 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/10. NumPy Index Arrays-93y6ms_fuQQ.mp4
1.2 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price--P5lMGuVA6U.mp4
1.2 MB
Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-xPDk70gKkjk.mp4
1.2 MB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/08. CONCAT-bCxZnQN28Y4.mp4
1.2 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error-ksf2wklgpZ8.mp4
1.2 MB
Part 13-Module 01-Lesson 07_Narrative Structures/52. D3 Hides Complexity-iNXkYbkD3IU.mp4
1.2 MB
Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-N5T8ouw1SGc.mp4
1.2 MB
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.mp4
1.2 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/27. The Update Function-z5f-oK0jwZk.mp4
1.2 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/09. Report CI Results-pr-2ZaCDzPY.mp4
1.2 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20-W0R3XOK1IfE.mp4
1.2 MB
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-wnIQ6fCVD40.mp4
1.2 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic-HruTS4wHpVQ.mp4
1.2 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling And EDA-EQXfxbUup0o.mp4
1.2 MB
Part 08-Module 01-Lesson 01_Conduct a Job Search/04. Open Yourself Up to Opportunity-1OamTNkk1xM.mp4
1.2 MB
Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-ZMfwPUrOFsE.mp4
1.2 MB
Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-31yCnTUNzts.mp4
1.2 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.mp4
1.2 MB
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.mp4
1.2 MB
Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-yLeLxDyXCSY.mp4
1.2 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.mp4
1.2 MB
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.mp4
1.2 MB
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-TpVxnYcI_uw.mp4
1.2 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/14. Dependent Variable-QyKOEh0722A.mp4
1.2 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import Solution-QnTPEAGXJaE.mp4
1.2 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-RF_DpOg--PY.mp4
1.2 MB
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.mp4
1.2 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.mp4
1.2 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/19. DISTINCT-YDJEHkgKORY.mp4
1.1 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-IJZs7KARtFo.mp4
1.1 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-IJZs7KARtFo.mp4
1.1 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/14. -E-Bd6EEl20s.mp4
1.1 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-TluBvgsphHQ.mp4
1.1 MB
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.mp4
1.1 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.mp4
1.1 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/21. Shape of Distribution When n Increases-YT3sdKcl3Vg.mp4
1.1 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/02. Introduction-fxNSn63xFvA.mp4
1.1 MB
Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.mp4
1.1 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/25. Rent - Decision-edm9jPvzeAc.mp4
1.1 MB
Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-eSZ1kr_yZFg.mp4
1.1 MB
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-r5qca6q4Fn4.mp4
1.1 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/08. Probability Mean or = 3-twcNden__9M.mp4
1.1 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-mFm0FfWHlXw.mp4
1.1 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.mp4
1.1 MB
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.mp4
1.1 MB
Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-9J3IwQFXveI.mp4
1.1 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.mp4
1.1 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results-tmAlVZCbgFA.mp4
1.1 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.mp4
1.1 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-obhHCeHpysw.mp4
1.1 MB
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-obhHCeHpysw.mp4
1.1 MB
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/24. Quiz Shape and Outliers (Visuals).html
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Part 17-Module 01-Lesson 16_Logistic Regression/05. Notebook + Quiz Fitting Logistic Regression in Python.html
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Part 21-Module 01-Lesson 05_Scripting/04. [For Windows] Configuring Git Bash to Run Python.html
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Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code.html
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/16. [Optional] Text Linear Model Assumptions.html
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Part 17-Module 01-Lesson 12_Hypothesis Testing/21. Quiz What is a p-value Anyway.html
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Part 17-Module 01-Lesson 16_Logistic Regression/30. Notebook + Quiz Model Diagnostics.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/22. Variability Example-gs4qKb-0Lfs.ar.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/28. Quiz Notation for the Mean.html
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Part 21-Module 01-Lesson 05_Scripting/28. Online Resources.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/18. Range Queries.html
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Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable.html
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Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts.html
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Part 15-Module 01-Lesson 02_Design Principles/07. Visualizing distributions.html
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Part 16-Module 02-Lesson 01_The Data Analysis Process/08. Packages Overview Quiz.html
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/04. Text Outline of Topics Covered.html
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/15. Homework 1 Final Quiz on Measures Spread.html
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Part 21-Module 01-Lesson 02_Data Types and Operators/34. Quiz More With Dictionaries.html
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/19. Notebook + Quiz Multicollinearity VIFs.html
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate.html
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Part 18-Module 02-Lesson 01_Gathering Data/09. HTML File Structure.html
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Part 13-Module 01-Lesson 07_Narrative Structures/06. Getting Data.html
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Part 13-Module 01-Lesson 07_Narrative Structures/64. All World Cup Games Recap.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/13. Binomial Distribution.html
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Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance.html
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Part 18-Module 02-Lesson 01_Gathering Data/17. JSON Files in Python.html
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Part 12-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier-qRv1wrtgsmM.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example.html
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Part 04-Module 01-Lesson 02_Jupyter notebooks/01. What are Jupyter notebooks.html
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/35. Quiz Dual Axis.html
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Part 09-Module 01-Lesson 07_Explore Many Variables/16. Sean's NFL Fan Sentiment Study-ahaxt6UKxQw.ar.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/05. Text Map of SQL Content.html
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Part 18-Module 02-Lesson 01_Gathering Data/10. HTML Files in Python.html
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/08. Inspecting Data Types.html
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Part 13-Module 01-Lesson 07_Narrative Structures/44. Parsing Overview and Parsing Attendance.html
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Part 21-Module 01-Lesson 02_Data Types and Operators/09. Quiz Integers and Floats.html
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Part 15-Module 01-Lesson 02_Design Principles/09. Other awesome graphs.html
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Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots.html
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Part 13-Module 01-Lesson 07_Narrative Structures/37. Visualize Every Game of the World Cup.html
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Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated.html
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Part 16-Module 03-Lesson 01_Basic SQL/45. Solutions AND and BETWEEN.html
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/24. Notebook + Quiz Bootstrapping.html
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Part 13-Module 01-Lesson 07_Narrative Structures/05. The Difficulty of Data Visualization.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/24. Solutions HAVING.html
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Part 16-Module 03-Lesson 02_SQL Joins/04. Text + Quiz Your First JOIN.html
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assets/css/fonts/KaTeX_Size2-Regular.ttf
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/28. Klout Sampling Distribution (Mean).html
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Part 16-Module 03-Lesson 01_Basic SQL/02. Video The Parch Posey Database.html
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Part 04-Module 01-Lesson 02_Jupyter notebooks/08. Magic keywords.html
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Part 17-Module 01-Lesson 12_Hypothesis Testing/29. Other Things to Consider - How Do CIs and HTs Compare.html
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Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size.html
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Part 13-Module 01-Lesson 05_Dimple.js/30. EDA vs Sketching Data Visualizations.html
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data.html
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Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages.html
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Part 21-Module 01-Lesson 03_Control Flow/26. Quiz Break, Continue.html
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/29. Klout Sampling Distribution (SD).html
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Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans().html
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/10. Intro to XLRD-TcWtpvLSoG0.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data.html
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/02. Text Installing Tableau.html
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Video Measures of Center (Mean).html
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Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/25. Empirical Variability Sanity Checking-6vxdVWIA6dI.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/41. Accuracy Using 1 of Features.html
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Part 15-Module 01-Lesson 02_Design Principles/14. Practical Rules for Using Color.html
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/04. Asking Questions.html
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Part 18-Module 02-Lesson 01_Gathering Data/16. JSON File Structure.html
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/38. Keyboards - Cohen's d.html
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/01. Video Introduction.html
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory.html
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean.html
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Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day.html
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Part 09-Module 01-Lesson 04_Problem Set Explore One Variable/05. Cheaper Diamonds.html
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/05. DF - Add to 10.html
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/26. Video DATE Functions II.html
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From.html
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test.html
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05.html
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Part 16-Module 03-Lesson 01_Basic SQL/01. Video SQL Introduction.html
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/27. Rent - CI.html
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Part 11-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram.html
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/21. Video Working With Outliers.html
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01.html
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/26. Rent - Cohen's d.html
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/02. Video Descriptive vs. Inferential Statistics.html
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel.html
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/43. Video Table Calculations.html
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject.html
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Part 17-Module 01-Lesson 13_Case Study AB tests/10. Metric - Enrollment Rate.html
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value.html
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/06. Quiz JOINs with Comparison Operators.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind.html
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/23. Video Marks Filters.html
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/40. Video Calculated Fields.html
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null.html
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Video The Shape For Data In The World.html
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data.html
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Part 05-Module 03-Lesson 01_Wrangle OpenStreetMap Data/Project Description - Wrangle OpenStreetMap Data.html
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Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys.html
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/01. Video What is Tableau.html
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Part 14-Module 01-Lesson 05_Analyzing Results/06. Checking Invariants, Part 2.html
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/36. Video Groups Sets.html
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions.html
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Video Two Useful Theorems - Central Limit Theorem.html
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/15. Filtering and Segmenting Example-XTS6m5_3fdU.ar.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Video Notation for the Mean.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price.html
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/11. Data Types (Continuous vs. Discrete).html
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Part 19-Module 01-Lesson 02_Design/15. Shape, Size, Other Tools.html
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Part 11-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule.html
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Part 16-Module 03-Lesson 02_SQL Joins/06. Text ERD Reminder.html
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/13. Video Worksheets.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots.html
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Part 17-Module 01-Lesson 14_Regression/12. Quiz What Defines A Line - Line Basics Quiz.html
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Part 21-Module 01-Lesson 02_Data Types and Operators/01. Introduction.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations.html
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Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major.html
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Part 12-Module 02-Lesson 05_Trees/11. Binary Tree Practice.html
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Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/11. Quiz MIN, MAX, AVG.html
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Part 11-Module 01-Lesson 09_Clustering/24. Clustering Changes.html
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Part 17-Module 01-Lesson 04_Probability/14. One Head 2.html
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/15. Conclusions Using Query.html
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/13. Video GROUP BY.html
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/20. Video Shape and Outliers.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/27. Quiz DATE Functions.html
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/05. Text Descriptive vs. Inferential Statistics.html
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Part 18-Module 03-Lesson 01_Assessing Data/12. Data Quality Dimensions 1.html
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Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2.html
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/02. Gambling in Vegas.html
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Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/06. Promoting Rock Music.html
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Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD.html
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Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/04. Video + Text First Aggregation - COUNT.html
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/15. Video Measures of Center (Median).html
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/01. Video What are Measures of Spread.html
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Part 21-Module 01-Lesson 04_Functions/05. Variable Scope.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision.html
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Part 16-Module 03-Lesson 02_SQL Joins/02. Video Why Would We Want to Split Data Into Separate Tables.html
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes.html
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Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure.html
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Part 11-Module 01-Lesson 12_Feature Selection/06. Example Buggy Feature.html
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Part 16-Module 03-Lesson 02_SQL Joins/21. Text Recap Looking Ahead.html
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Part 17-Module 01-Lesson 12_Hypothesis Testing/01. Introduction.html
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Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds.html
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis.html
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis.html
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Part 11-Module 01-Lesson 15_Evaluation Metrics/44. Metrics for Your POI Identifier.html
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/04. 11. Which Are Not Constructs.html
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean.html
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Part 11-Module 01-Lesson 03_SVM/33. Optimize C Parameter.html
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Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection.html
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/07. Filter, Drop Nulls, Dedupe.html
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Part 11-Module 01-Lesson 13_PCA/28. PCA in sklearn.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/05. SD for Meal Price.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/16. D3 Chaining Syntax.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/20. Absolute or Relative Difference.html
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/25. Create a Radius Scale.html
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size.html
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average.html
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Part 21-Module 01-Lesson 03_Control Flow/33. Solution List Comprehensions.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example.html
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/07. Text General Notes for Building Stories.html
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/19. Quiz On Visual Encodings.html
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/20. Video When Does the Central Limit Theorem Not Work.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/28. Server Requests and D3.html
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Part 04-Module 02-Lesson 01_Data Analysis Process/02. Problems Solved by Data Analysts.html
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Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R.html
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/15. Quiz COALESCE.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/02. Technical Interlude.html
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Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250.html
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Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean.html
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Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size.html
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Part 21-Module 01-Lesson 04_Functions/15. [Optional] Quiz Iterators and Generators.html
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Part 07-Module 01-Lesson 01_GitHub Review/Project Description - Optimize Your GitHub Profile.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/22. D3 Scale Syntax.html
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Part 12-Module 02-Lesson 08_Technical Interview - Python/07. Coding-zhQYREUI8Z0.en-US.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution.html
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Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median.html
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/28. Data Wrangling Summary.html
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Part 18-Module 03-Lesson 01_Assessing Data/09. Quality Visual Assessment 1.html
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Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/12. Adjustments - price vs. volume.html
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Part 21-Module 01-Lesson 05_Scripting/05. Running a Python Script.html
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Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up.html
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Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect.html
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Part 13-Module 01-Lesson 05_Dimple.js/16. Debugging and Inspecting Chart Objects.html
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Part 21-Module 01-Lesson 04_Functions/03. Quiz Defining Functions.html
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution.html
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/07. Quiz SUM.html
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Part 21-Module 01-Lesson 04_Functions/12. Quiz Lambda Expressions.html
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Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo.html
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/16. Pandas groupby()-smBMJlpWdVI.ar.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/05. Fundamentals of XML-Ti8K9FmNW1w.ar.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day.html
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Part 16-Module 03-Lesson 02_SQL Joins/12. Solutions JOIN Questions Part I.html
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Part 04-Module 01-Lesson 02_Jupyter notebooks/06. Markdown cells.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day.html
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Part 11-Module 01-Lesson 03_SVM/30. A Smaller Training Set.html
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Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables.html
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Part 09-Module 01-Lesson 07_Explore Many Variables/16. Sean's NFL Fan Sentiment Study-ahaxt6UKxQw.ja.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables.html
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/26. Wrangling vs. EDA vs. ETL.html
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Part 04-Module 03-Lesson 01_Investigate a Dataset/02. Project Details.html
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Part 05-Module 02-Lesson 02_Problem Set Data and Tables/09. Interpreting Schema.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision.html
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Part 03-Module 01-Lesson 29_PS 10b t-Tests, Part 2/07. 18. Cell Phone Law Difference Scores.html
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Part 12-Module 02-Lesson 08_Technical Interview - Python/14. Project Description.html
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Part 13-Module 01-Lesson 05_Dimple.js/11. Chart Layout and Group Tags.html
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Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI.html
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Part 09-Module 01-Lesson 07_Explore Many Variables/06. Wide and Long Format.html
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Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment.html
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Part 05-Module 02-Lesson 02_Problem Set Data and Tables/05. Welcome to SQLite!.html
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Part 11-Module 01-Lesson 12_Feature Selection/29. Remove, Repeat.html
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/03. Quiz FULL OUTER JOIN.html
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Part 05-Module 01-Lesson 05_Data Quality/11. Auditing a Cross-Field Constraint.html
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Part 18-Module 02-Lesson 01_Gathering Data/10. HTML Files In Python 2-3caDGTxcoCw.ar.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/02. Video Histograms.html
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Part 13-Module 01-Lesson 05_Dimple.js/07. Javascript Debugger.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/14. Filtering and Segmenting-DETCNMqnnKw.ar.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/30. Checking Important Features Again.html
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Part 13-Module 01-Lesson 05_Dimple.js/09. Inspecting Variables and Data.html
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Part 17-Module 01-Lesson 12_Hypothesis Testing/20. Video Calculating the p-value.html
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Part 21-Module 01-Lesson 05_Scripting/08. Scripting with Raw Input.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/16. Video GROUP BY Part II.html
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Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words.html
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Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2.html
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score.html
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Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI.html
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/18. 26. Video Games.html
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Part 15-Module 01-Lesson 02_Design Principles/17. Bad Visual Quizzes.html
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Part 11-Module 01-Lesson 03_SVM/29. SVM Author ID Timing.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/33. Adding Bars and Text.html
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Part 12-Module 02-Lesson 01_Introduction and Efficiency/11. Efficiency Practice.html
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Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier.html
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Part 09-Module 02-Lesson 01_Explore and Summarize Data/Project Description - Explore and Summarize Data.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Video Window Functions 1.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/17. Removing Elements with D3.html
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Part 07-Module 01-Lesson 01_GitHub Review/10. Commit messages best practices.html
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Part 09-Module 01-Lesson 04_Problem Set Explore One Variable/09. Price per Carat by Cut.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/26. Up and Down the Visualization Spectrum-NdVf2bY8OnM.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows.html
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Part 04-Module 01-Lesson 02_Jupyter notebooks/04. Notebook interface.html
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Part 17-Module 01-Lesson 14_Regression/05. Quiz Linear Regression Language.html
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Part 03-Module 01-Lesson 20_L8 Estimation/23. CI Bounds.html
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries.html
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Part 21-Module 01-Lesson 02_Data Types and Operators/33. Solution Dictionaries and Identity Operators.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/09. CSS Class Selectors.html
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Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/14. Changing the Title.html
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/07. Matrix Multiplication Part 2-8jtk8BzBdj8.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/18. Better Sample.html
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/08. Video Standard Deviation Calculation.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample.html
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Part 17-Module 01-Lesson 14_Regression/08. Correlation Coefficients.html
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Part 18-Module 03-Lesson 01_Assessing Data/03. Dataset Oral Insulin Phase II Clinical Trial Data.html
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Part 21-Module 01-Lesson 02_Data Types and Operators/04. Solution Arithmetic Operators.html
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Part 17-Module 01-Lesson 11_Confidence Intervals/15. Correct Interpretations of Confidence Intervals.html
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Part 21-Module 01-Lesson 02_Data Types and Operators/12. Solution Booleans, Comparison and Logical Operators.html
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Part 17-Module 01-Lesson 13_Case Study AB tests/15. Quiz Analyzing Multiple Metrics.html
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/05. Screencast + Text How Does MLR Work.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/17. Quiz Comparing a Row to Previous Row.html
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Part 10-Module 01-Lesson 02_LinkedIn Review/01. Using LinkedIn.html
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan.html
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Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs.html
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not.html
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Part 11-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses.html
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Part 17-Module 01-Lesson 16_Logistic Regression/09. Video Model Diagnostics + Performance Metrics.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not.html
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Part 21-Module 01-Lesson 03_Control Flow/19. Solution Iterating Through Dictionaries.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values.html
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Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text.html
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Part 09-Module 01-Lesson 02_R Basics/01. The Power of R.html
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Part 05-Module 02-Lesson 03_Elements of SQL/07. The One Thing SQL is Terrible At.html
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Part 03-Module 01-Lesson 08_L3 Central Tendency/09. Mode of Categorical Data.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/14. Dependent Variable.html
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Part 11-Module 01-Lesson 06_Datasets and Questions/25. Follow the Money.html
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Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test.html
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/09. Text Dummy Variables.html
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Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable.html
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/04. Examples.html
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values.html
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Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset.html
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Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters.html
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Part 12-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-i3RTW83wI1Q.zh-CN.vtt
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/09. 25. Caffeine.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning.html
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Part 21-Module 01-Lesson 02_Data Types and Operators/37. Solution Compound Data Structions.html
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Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/19. Sensitivity and Robustness Example-_I7m7Y4hBOs.ar.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/03. Accuracy vs. Training Set Size-9w1Yi5nMNgw.ar.vtt
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Part 11-Module 01-Lesson 13_PCA/21. Info Loss and Principal Components.html
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Part 18-Module 04-Lesson 01_Cleaning Data/07. Quiz and Solution Notebooks.html
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Part 07-Module 01-Lesson 01_GitHub Review/Project Rubric - Optimize Your GitHub Profile.html
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Part 15-Module 01-Lesson 04_Telling Stories with Tableau/04. Building a Dashboard.html
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Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean.html
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Part 13-Module 01-Lesson 05_Dimple.js/34. Summary of Dimple and Chart Types.html
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Part 11-Module 01-Lesson 13_PCA/23. PCA for Feature Transformation.html
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Video The Background of Bootstrapping.html
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Part 12-Module 01-Lesson 05_Interview Practice/Project Rubric - Interview Practice (Data Analyst).html
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Part 11-Module 01-Lesson 12_Feature Selection/28. Use TfIdf to Get the Most Important Word.html
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/08. Video Dummy Variables.html
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Video Measures of Center (Mode).html
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Part 17-Module 01-Lesson 14_Regression/03. Quiz Machine Learning Big Picture.html
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety.html
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Part 11-Module 01-Lesson 03_SVM/38. Final Thoughts on Deploying SVMs.html
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Part 11-Module 01-Lesson 13_PCA/06. PCA for Data Transformation.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic.html
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/10. Transposes in NumPy.html
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment.html
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Part 05-Module 02-Lesson 02_Problem Set Data and Tables/01. WARM UP - Chinook Query Playground.html
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/14. Quiz WITH.html
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Part 14-Module 01-Lesson 05_Analyzing Results/06. Checking Invariants, Part 2-05jVh4kUbHU.ar.vtt
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/05. Element-wise Operations in NumPy.html
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution.html
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Part 13-Module 02-Lesson 01_Make Effective Data Visualization/01. Project Overview.html
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Part 03-Module 01-Lesson 11_L4 Variability/02. Should You Get an Account.html
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values.html
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/02. Video Multiple Linear Regression.html
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Part 11-Module 01-Lesson 13_PCA/25. ReviewDefinition of PCA.html
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Video Introduction to Sampling Distributions Part III.html
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Part 11-Module 01-Lesson 03_SVM/28. SVM Author ID Accuracy.html
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Part 11-Module 01-Lesson 03_SVM/35. Optimized RBF vs. Linear SVM Accuracy.html
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Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling.html
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Part 11-Module 01-Lesson 13_PCA/26. Applying PCA to Real Data.html
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Part 11-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro.html
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Part 18-Module 04-Lesson 01_Cleaning Data/17. Flashforward-rfMu3f9O9hQ.zh-CN.vtt
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Part 15-Module 01-Lesson 02_Design Principles/04. Chart Relationships 1.html
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/24. Video Better Way.html
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price.html
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/11. Fixing Data Types Pt 3.html
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Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins.html
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Part 12-Module 02-Lesson 05_Trees/14. BST Practice.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/22. Variability Example-gs4qKb-0Lfs.zh-CN.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/02. Defining Data Visualization.html
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Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/17. Summary Metrics Example.html
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Part 16-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts.html
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/05. Good vs. Bad Data Viz Examples.html
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Part 21-Module 01-Lesson 03_Control Flow/22. Solution While Loops Practice.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/01. D3 version notice.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/03. Video NULLs and Aggregation.html
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Part 21-Module 01-Lesson 04_Functions/14. [Optional] Iterators and Generators.html
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Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands).html
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Part 21-Module 01-Lesson 02_Data Types and Operators/38. Conclusion.html
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Why use data visualization.html
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Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2.html
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Part 15-Module 01-Lesson 02_Design Principles/05. Chart Relationships 2.html
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Part 17-Module 01-Lesson 14_Regression/14. Text The Regression Closed Form Solution.html
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Part 13-Module 01-Lesson 07_Narrative Structures/index.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis.html
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Part 13-Module 01-Lesson 05_Dimple.js/28. Changing the Chart Type.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting.html
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Part 16-Module 03-Lesson 02_SQL Joins/14. Video LEFT and RIGHT JOINs.html
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Part 11-Module 01-Lesson 13_PCA/29. When to Use PCA.html
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Part 11-Module 01-Lesson 13_PCA/31. Eigenfaces Code.html
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/22. Video Bootstrapping.html
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Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic.html
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Part 06-Module 01-Lesson 03_Analyzing Data/19. Geospatial Indexes-iGnSNfzaLf4.zh-CN.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/06. Video Multiple Linear Regression Model Results.html
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Part 19-Module 01-Lesson 02_Design/09. Design Integrity.html
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Part 12-Module 02-Lesson 03_Searching and Sorting/05. Recursion Practice.html
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/06. Video What if We Only Want One Number.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI.html
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/15. Merging Datasets.html
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Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing.html
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/08. 10. Which Are Constructs.html
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/06. Critical Regions.html
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity.html
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/03. Video Weekdays vs. Weekends What is the Difference.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/16. Data Types.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/28. Meaningful Results.html
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Part 12-Module 02-Lesson 01_Introduction and Efficiency/06. Python The Basics.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/30. Further Study.html
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Video Why the Standard Deviation.html
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Part 11-Module 01-Lesson 06_Datasets and Questions/32. Missing POIs 4 (optional).html
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency.html
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Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/05. Adjustments - price vs. depth.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/29. Let's Make a Bar Chart.html
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Part 13-Module 01-Lesson 05_Dimple.js/19. Adding the Series and Drawing the Chart.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/25. Video DATE Functions.html
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Part 04-Module 02-Lesson 01_Data Analysis Process/25. Correlation Does Not Imply Causation.html
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Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization.html
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Part 16-Module 02-Lesson 04_Programming Workflow for Data Analysis/02. Analyzing with IPython.html
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Video Summary.html
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Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1.html
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2.html
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2.html
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Part 09-Module 01-Lesson 03_Explore One Variable/06. Estimating Your Audience Size.html
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Part 21-Module 01-Lesson 02_Data Types and Operators/18. Solution Type and Type Conversion.html
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Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score.html
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/08. Video Data Types (Continuous vs. Discrete).html
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Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers.html
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization.html
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Part 18-Module 03-Lesson 01_Assessing Data/14. Programmatic Assessment.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis.html
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Part 11-Module 01-Lesson 12_Feature Selection/23. Overfitting a Decision Tree 1.html
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line.html
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Part 11-Module 01-Lesson 03_SVM/32. Deploy an RBF Kernel.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/14. Acne Medication - Decision.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Video Percentiles.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/26. Up and Down the Visualization Spectrum.html
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/05. Write the Body.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values.html
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Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/15. Mini-Project 1 RAW Visualization.html
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/05. Text Subquery Formatting.html
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/09. Video MIN MAX.html
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship.html
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Part 21-Module 01-Lesson 03_Control Flow/01. Introduction.html
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Part 18-Module 04-Lesson 01_Cleaning Data/03. Dataset Oral Insulin Phase II Clinical Trial Data.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error.html
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Part 13-Module 01-Lesson 05_Dimple.js/13. Adding an Axis with Dimple.html
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Part 11-Module 01-Lesson 03_SVM/16. Visualizing the New Feature.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/19. Video DISTINCT.html
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Part 11-Module 01-Lesson 03_SVM/37. How Many Chris Emails Predicted.html
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/18. Assess (Summary).html
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Part 11-Module 01-Lesson 06_Datasets and Questions/04. Downloading Enron Data-TgkBAtaTqJk.ar.vtt
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/10. 27. English Teaching.html
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/16. Solutions COALESCE.html
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Part 06-Module 01-Lesson 03_Analyzing Data/15. Multiple Stages Using a Given Operator-0TV8kTw9-HM.ar.vtt
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/28. 49. Depression.html
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/37. Increase Engagement.html
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Part 12-Module 02-Lesson 04_Maps and Hashing/03. Python Dictionaries.html
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Part 11-Module 01-Lesson 06_Datasets and Questions/13. Size of the Enron Dataset.html
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Part 18-Module 02-Lesson 01_Gathering Data/10. HTML Files in Python 1-0VZumC18UvQ.ar.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/31. What Do You Get with a Good Klout Score.html
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Part 11-Module 01-Lesson 06_Datasets and Questions/18. Query the Dataset 1.html
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Part 04-Module 02-Lesson 01_Data Analysis Process/24. Are your Results Just Noise.html
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Part 09-Module 01-Lesson 07_Explore Many Variables/16. Sean's NFL Fan Sentiment Study-ahaxt6UKxQw.zh-CN.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/07. Video Data Types (Ordinal vs. Nominal).html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma.html
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate.html
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Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/09. price vs. volume.html
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Part 11-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/21. Rankings of Visual Encodings.html
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Part 13-Module 01-Lesson 05_Dimple.js/10. Dimple Axes, Series and Fields.html
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Part 11-Module 01-Lesson 03_SVM/11. SVM Decision Boundary.html
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Part 12-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-i3RTW83wI1Q.pt-BR.vtt
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Part 15-Module 01-Lesson 02_Design Principles/02. Common Chart Types.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/20. Quiz DISTINCT.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/30. Code Structure and JavaScript.html
9.1 kB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs.html
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Part 12-Module 02-Lesson 03_Searching and Sorting/04. Recursion-_aI2Jch6Epk.pt-BR.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200.html
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Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210.html
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Part 06-Module 01-Lesson 03_Analyzing Data/11. Unwind Operator-6wBjB3Ca5H4.pt-BR.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/10. Assessing vs. Exploring.html
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Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression.html
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Part 03-Module 01-Lesson 11_L4 Variability/39. Clarifying Sample SD.html
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Part 17-Module 01-Lesson 16_Logistic Regression/31. Video Final Thoughts On Shifting to Machine Learning.html
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/17. Screencast Multicollinearity VIFs.html
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/22. Simulation Applet.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/25. Empirical Variability Sanity Checking.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/32. Compute CI.html
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Part 21-Module 01-Lesson 03_Control Flow/12. Solution For Loops Practice.html
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Part 17-Module 01-Lesson 11_Confidence Intervals/10. Video Traditional Confidence Intervals.html
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions.html
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/22. Decomposing Visualizations.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/34. From Source Code to Graphic.html
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Part 17-Module 01-Lesson 12_Hypothesis Testing/32. Hypothesis Testing Conclusion.html
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Part 13-Module 01-Lesson 05_Dimple.js/03. World Cup Sketch.html
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Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/05. Best Customer Emails.html
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/10. Video AVG.html
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic.html
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Part 11-Module 01-Lesson 06_Datasets and Questions/15. Finding POIs in the Enron Data.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/10. Techniques to Gather Additional Data.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/26. Empirical Confidence Intervals.html
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Part 12-Module 01-Lesson 05_Interview Practice/02. Quiz Analyzing an Interview.html
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Part 11-Module 01-Lesson 03_SVM/01. Welcome to SVM.html
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Part 11-Module 01-Lesson 03_SVM/10. SVM in SKlearn.html
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Part 11-Module 01-Lesson 03_SVM/13. Nonlinear SVMs.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/09. Other Techniques, Part 2-siuolDaB4eU.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/05. Walkthrough and Dataset.html
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages.html
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Part 03-Module 01-Lesson 08_L3 Central Tendency/26. Use Measures of Center to Compare.html
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Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1.html
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Part 17-Module 01-Lesson 12_Hypothesis Testing/07. Types of Errors - Part I.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/21. t-Critical.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/30. Video CASE Aggregations.html
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Part 11-Module 01-Lesson 06_Datasets and Questions/27. Dealing with Unfilled Features.html
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Part 17-Module 01-Lesson 16_Logistic Regression/04. Video Fitting Logistic Regression in Python.html
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/03. A Definition and An Analogy.html
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Part 21-Module 01-Lesson 05_Scripting/19. Solution Reading and Writing Files.html
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Part 11-Module 01-Lesson 06_Datasets and Questions/16. How Many POIs Exist.html
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Part 12-Module 02-Lesson 08_Technical Interview - Python/12. Next Steps.html
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/08. t-Table.html
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Part 09-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset.html
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price.html
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Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error.html
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Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating.html
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Part 21-Module 01-Lesson 03_Control Flow/27. Solution Break, Continue.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region.html
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Part 11-Module 01-Lesson 06_Datasets and Questions/12. Datasets and Questions Mini-Project.html
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Part 17-Module 01-Lesson 16_Logistic Regression/07. Video (ScreenCast) Interpret Results - Part II.html
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data.html
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Part 17-Module 01-Lesson 12_Hypothesis Testing/02. Hypothesis Testing.html
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Video Why are Sampling Distributions Important.html
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Part 12-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array.html
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Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram.html
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Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters.html
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Part 11-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter.html
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/02. Data Has Dimensions-F4NSv776X0c.pt-BR.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/27. Statistically Significant.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/06. Video SUM.html
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/12. 16. Which Are Hypotheses.html
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/26. Klout.html
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=.html
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Part 17-Module 01-Lesson 16_Logistic Regression/01. Video Introduction.html
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Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors.html
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/14. Scatter Plot wMultiple Dimensions.html
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Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning.html
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/21. 37. Insomnia.html
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/11. Correlation Coefficients.html
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Part 17-Module 01-Lesson 16_Logistic Regression/02. Video Fitting Logistic Regression.html
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Part 11-Module 01-Lesson 06_Datasets and Questions/20. Query the Dataset 3.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/32. Binding Data.html
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Part 05-Module 03-Lesson 01_Wrangle OpenStreetMap Data/01. Project Overview.html
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Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means.html
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Part 17-Module 01-Lesson 04_Probability/13. One Head 1.html
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Part 12-Module 02-Lesson 04_Maps and Hashing/10. String Keys Practice.html
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Part 12-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes.html
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/09. SQL Subquery Video-10pmKmTI_CA.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age.html
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60.html
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/10. Quiz Subquery Mania.html
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Part 11-Module 01-Lesson 12_Feature Selection/09. Univariate Feature Selection.html
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Part 11-Module 01-Lesson 12_Feature Selection/31. Accuracy of the Overfit Tree.html
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Part 11-Module 01-Lesson 06_Datasets and Questions/04. Downloading Enron Data.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/15. Solutions Aliases for Multiple Window Functions.html
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Part 16-Module 03-Lesson 02_SQL Joins/10. Video Alias.html
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Part 04-Module 01-Lesson 01_Anaconda/05. Managing environments.html
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Part 16-Module 01-Lesson 01_Anaconda/05. Managing environments.html
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/11. Video CAST.html
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Part 10-Module 01-Lesson 03_Udacity Professional Profile/03. Customizing Your Profile.html
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/08. 24. Classical Music.html
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60.html
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Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2.html
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Part 21-Module 01-Lesson 04_Functions/08. Documentation.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements.html
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Part 17-Module 01-Lesson 04_Probability/03. Fair Coin.html
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Part 17-Module 01-Lesson 16_Logistic Regression/06. Video Interpreting Results - Part I.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM.html
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Part 13-Module 01-Lesson 05_Dimple.js/20. Object Oriented Design and Charts.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/22. Solutions Percentiles.html
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Video Data Types (Quantitative vs. Categorical).html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/24. Calculate Pooled Variance.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/03. Metric Definition Overview, Part 2.html
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/25. Using Sampling Distribution.html
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Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rule.html
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/25. Congratulations and Next Steps.html
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data.html
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/14. Video Other Sampling Distributions.html
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size.html
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Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular.html
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information.html
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/40. Notation for Difference.html
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/18. Video JOINing Subqueries.html
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Part 11-Module 01-Lesson 03_SVM/27. SVM Mini-Project.html
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Part 14-Module 01-Lesson 05_Analyzing Results/09. Single Metric Example--QwMdwqUq9c.ar.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom.html
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Part 17-Module 01-Lesson 04_Probability/18. Doubles.html
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Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size.html
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Part 11-Module 01-Lesson 12_Feature Selection/24. Overfitting a Decision Tree 2.html
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Part 12-Module 02-Lesson 08_Technical Interview - Python/Project Rubric - Technical Interview Practice.html
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Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression.html
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Part 13-Module 01-Lesson 05_Dimple.js/31. Customizing a Dimple Chart.html
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Video Introduction to Notation.html
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/23. MMs.html
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Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4.html
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/11. Data Vis in Data Science.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference.html
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/13. One-Sample t-Test.html
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/31. Dependent Samples.html
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/08. NumPy Matrix Multiplication.html
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/02. Data Has Dimensions-F4NSv776X0c.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/41. Types of Designs.html
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Part 03-Module 01-Lesson 11_L4 Variability/07. Chop Off the Tails.html
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Part 03-Module 01-Lesson 11_L4 Variability/30. Standard Deviation.html
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Part 12-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier.html
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Part 17-Module 01-Lesson 16_Logistic Regression/33. Video Congratulations.html
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Part 09-Module 01-Lesson 04_Problem Set Explore One Variable/13. Carat Frequency Polygon.html
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Part 13-Module 01-Lesson 05_Dimple.js/15. The Benefits of Dimple.html
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/08. Defining Metrics Other Techniques.html
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/07. DF - Sample SD.html
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Part 11-Module 01-Lesson 12_Feature Selection/26. Accuracy of Your Overfit Decision Tree.html
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies.html
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Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1.html
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Part 11-Module 01-Lesson 14_Validation/17. Your First (Overfit) POI Identifier.html
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Part 09-Module 01-Lesson 07_Explore Many Variables/16. Sean's NFL Fan Sentiment Study.html
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Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key.html
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Part 16-Module 02-Lesson 01_The Data Analysis Process/07. Packages Overview.html
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/09. Quiz Self JOINs.html
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Part 13-Module 01-Lesson 05_Dimple.js/33. Advantages with CSS.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/15. Why Even Create Graphics.html
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Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8.html
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Part 15-Module 01-Lesson 04_Telling Stories with Tableau/07. Stories.html
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Part 11-Module 01-Lesson 06_Datasets and Questions/28. Dict-to-array conversion.html
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Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API.html
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Part 13-Module 01-Lesson 05_Dimple.js/27. Bar Chart The Bad.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/05. Quiz Window Functions 2.html
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Part 03-Module 01-Lesson 11_L4 Variability/35. Point of SD.html
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Part 03-Module 01-Lesson 11_L4 Variability/40. Jelly Beans.html
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/04. Data Types.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/06. Solutions Window Functions 2.html
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Part 11-Module 01-Lesson 06_Datasets and Questions/11. Enron Dataset Mini-Project Video.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/11. Other Techniques Example-z1UX9i9_piQ.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/30. Conclusion.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/22. SEM.html
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. Video JOINs with Comparison Operators.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/29. Cohen's d.html
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Part 11-Module 01-Lesson 06_Datasets and Questions/01. Introduction.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/03. Metric Definition Overview, Part 2-0DyLzS2ux7g.ar.vtt
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/09. 12. Define Operational Definition.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/13. Explanatory vs Exploratory.html
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Part 09-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations.html
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Part 17-Module 01-Lesson 07_Bayes Rule/29. Generalizing.html
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Part 11-Module 01-Lesson 09_Clustering/21. Clustering with 3 Features.html
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post.html
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Part 21-Module 01-Lesson 05_Scripting/16. Accessing Error Messages.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/25. Dot Notation-OcPW6xp8DfE.ar.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/35. Visualization and D3 Basics.html
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/04. Write the Introduction.html
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Part 04-Module 02-Lesson 01_Data Analysis Process/32. Survey Says!.html
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/22. 38. Insomnia.html
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Part 21-Module 01-Lesson 05_Scripting/01. Introduction.html
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Part 17-Module 01-Lesson 14_Regression/02. Video Introduction to Machine Learning.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/24. The Facebook Offering Animation.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/30. r^2.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/03. Valid MongoDB Documents.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/03. Quiz Window Functions 1.html
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Part 17-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/05. Video COUNT NULLs.html
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Part 16-Module 02-Lesson 01_The Data Analysis Process/05. DAP Overview-qdV4sifMmWI.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/34. Prone to Misinterpretations.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/01. Intro.html
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/12. Dual Axis.html
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Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4.html
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Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5.html
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Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/18. Solutions Comparing a Row to Previous Row.html
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Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/07. Supported Data Models.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/08. Quiz ROW_NUMBER RANK.html
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place.html
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/21. One tailed or two tailed.html
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Part 17-Module 01-Lesson 14_Regression/16. Video How to Interpret the Results.html
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Part 11-Module 01-Lesson 12_Feature Selection/16. Lasso Regression.html
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Part 03-Module 01-Lesson 13_L5 Standardizing/03. Absolute or Relative.html
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Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1.html
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Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/19. Sensitivity and Robustness Example.html
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/03. Video Welcome!.html
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/05. BBC Memory Test.html
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Part 04-Module 02-Lesson 01_Data Analysis Process/29. Data Analysis and Related Terms.html
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Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/05. BBC Memory Test.html
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Part 11-Module 01-Lesson 12_Feature Selection/15. Regularization.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/12. Metric Definition and Data Capture.html
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/12. Internal Process.html
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar.html
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Part 18-Module 02-Lesson 01_Gathering Data/24. Other File Formats.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/14. Anscombe’s Quartet.html
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Part 17-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion.html
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/15. JSON Playground-la_rboWWjQI.zh-CN.vtt
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/05. 15. Variable Relationships.html
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Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3.html
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/07. Google Account.html
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Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys.html
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Part 17-Module 01-Lesson 07_Bayes Rule/32. Reducing Uncertainty.html
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Part 04-Module 02-Lesson 01_Data Analysis Process/19. Lessons Completed in First Week -nZq-Y2lfjpY.ar.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/17. Exploring Student Engagement.html
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Part 11-Module 01-Lesson 09_Clustering/22. Stock Option Range.html
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Part 09-Module 01-Lesson 03_Explore One Variable/09. Be Skeptical of Outliers and Anomalies.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/07. Google Account.html
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Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API.html
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Video Introduction to Summary Statistics.html
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/36. Hypothesis Testing.html
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Part 11-Module 01-Lesson 12_Feature Selection/22. Feature Selection Mini-Project.html
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/12. 29. Extreme Temperature.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/13. Manipulating DOM Nodes.html
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Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution.html
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Part 12-Module 02-Lesson 02_List-Based Collections/04. Python Lists.html
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations.html
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Part 17-Module 01-Lesson 14_Regression/17. Video Does the Line Fit the Data Well.html
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Part 09-Module 01-Lesson 04_Problem Set Explore One Variable/06. Price by Cut Histograms.html
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Part 17-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data.html
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Part 09-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes.html
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/11. 28. Reading Score.html
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Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions.html
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Part 05-Module 01-Lesson 05_Data Quality/10. Wikipedia Infobox Dataset-hpyNAYJODqw.ar.vtt
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Part 12-Module 02-Lesson 06_Graphs/05. Graph Practice.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/21. Adding SVG Elements.html
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Part 17-Module 01-Lesson 11_Confidence Intervals/05. ScreenCast Difference In Means.html
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Part 09-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation.html
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/07. Show me.html
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Part 03-Module 01-Lesson 13_L5 Standardizing/20. SD of Standardized Distribution.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/05. Refining the Customer Funnel.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/29. Survey Says!.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/05. Introduction to D3.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/24. Empirical Variability-Wzs1KFldiUE.ar.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/01. Intro to MongoDB.html
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Part 09-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width.html
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/04. NumPy Arrays-UG924zKZF7U.ar.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/05. NumPy Arrays-UG924zKZF7U.ar.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/01. Intro.html
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/04. Probability Greater.html
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Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/04. Countries with most Invoices.html
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Part 11-Module 01-Lesson 11_Text Learning/19. Clean Away Signature Words.html
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Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score.html
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Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/01. price vs. x.html
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Part 15-Module 01-Lesson 02_Design Principles/10. Pre-Attentive Processing.html
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/02. Metric Definition Overview.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/18. Sensitivity and Robustness.html
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/03. Quiz LEFT RIGHT.html
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/06. 19. n.html
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Part 04-Module 02-Lesson 01_Data Analysis Process/03. Data Analysis Process.html
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Part 12-Module 02-Lesson 03_Searching and Sorting/04. Recursion-_aI2Jch6Epk.zh-CN.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/20. How Scales Work.html
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Part 21-Module 01-Lesson 05_Scripting/21. The Standard Library.html
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/11. In-Place vs. Not In-Place.html
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Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3.html
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/15. Hypotheses.html
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Part 21-Module 01-Lesson 04_Functions/11. Lambda Expressions.html
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Part 19-Module 01-Lesson 02_Design/02. Lesson Overview.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/09. Other Techniques, Part 2.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/14. Filtering and Segmenting.html
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/02. Video Introduction to NULLs.html
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Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords.html
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Part 03-Module 01-Lesson 20_L8 Estimation/27. Results from Sample.html
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/30. Lessons Learned, Part 2.html
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Part 16-Module 03-Lesson 02_SQL Joins/15. Text Other JOIN Notes.html
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/22. Golden Arches Theory.html
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Part 18-Module 03-Lesson 01_Assessing Data/19. How Data Gets Dirty and Messy.html
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Part 11-Module 01-Lesson 09_Clustering/19. Clustering Features.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/22. Golden Arches Theory.html
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Part 12-Module 02-Lesson 04_Maps and Hashing/07. Load Factor.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/12. Solutions Aggregates in Window Functions.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/28. Server Requests and D3-Lx9dhgMZO1s.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar.html
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics.html
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Part 18-Module 03-Lesson 01_Assessing Data/20. You Can Iterate!.html
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Part 04-Module 02-Lesson 01_Data Analysis Process/07. Fixing Data Types.html
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Part 04-Module 02-Lesson 01_Data Analysis Process/16. Indulge Curiosity.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge.html
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Part 05-Module 01-Lesson 05_Data Quality/08. Example Using our Blueprint-G3RjHqqQSgE.en.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/23. Nonparametric Answers.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/24. Empirical Variability.html
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Part 05-Module 01-Lesson 05_Data Quality/08. Example Using our Blueprint-G3RjHqqQSgE.en-US.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/20. Recap.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/33. Text Recap.html
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Part 17-Module 01-Lesson 11_Confidence Intervals/12. Video Other Language Associated with Confidence Intervals.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/02. Standard Error.html
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/08. Intro to PyMongo.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/09. Solutions ROW_NUMBER RANK.html
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/20. 36. Student Satisfaction.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/10. Estimating Click-Through-Probability.html
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/20. Practice Viz Top Skills.html
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Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/01. Data Visualization Resources-OYl-saB2vWE.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/22. How Page Views Affect Sensitivity.html
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Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight.html
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Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/11. Gapminder Multivariate Analysis.html
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/04. Solutions Write Your First Subquery.html
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Part 17-Module 01-Lesson 11_Confidence Intervals/14. Video Correct Interpretations of Confidence Intervals.html
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/19. 40. Random Assignment.html
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Part 11-Module 01-Lesson 14_Validation/10. Practical Advice for K-Fold in sklearn.html
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Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4.html
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Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/03. 9. Common Decade.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/15. Using mongoimport.html
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/21. 42. Why Placebo.html
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/26. 47. Causality.html
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Part 03-Module 01-Lesson 08_L3 Central Tendency/14. Helpful Symbols.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/01. What is Data Visualization.html
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Part 17-Module 01-Lesson 11_Confidence Intervals/08. Video Statistical vs. Practical Significance.html
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/03. 8. SAT Scores.html
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/14. What is the Question.html
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Part 09-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps.html
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/22. Screencast How to Add Higher Order Terms.html
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Part 11-Module 01-Lesson 14_Validation/13. GridSearchCV in sklearn.html
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Part 14-Module 01-Lesson 06_Final Project/04. Calculating Standard Deviation.html
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Part 19-Module 01-Lesson 02_Design/19. Same Data, Different Stories.html
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/06. BBC Scores.html
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/12. Plot Colors for Qualitative Factors.html
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Part 09-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/21. Size vs. Power Trade-Off.html
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Part 03-Module 01-Lesson 20_L8 Estimation/20. Hypothesis Testing Song.html
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Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/05. Proportion of Friendships Initiated.html
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/04. Solutions FULL OUTER JOIN.html
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Part 16-Module 03-Lesson 02_SQL Joins/13. Video Motivation for Other JOINs.html
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk.html
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Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/02. Question 2.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/04. Define Constructs.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/07. History of AB Testing.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/18. Comparing Two Samples.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/19. Pooled Standard Error.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/06. Words of Wisdom from Zipfian Academy.html
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Part 21-Module 01-Lesson 05_Scripting/23. Solution The Standard Library.html
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Part 04-Module 03-Lesson 01_Investigate a Dataset/Project Description - Investigate a Dataset.html
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Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/12. Mystery Code.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/14. Confidence Intervals.html
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Part 16-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions.html
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/09. Scatter Plots.html
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Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias.html
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Part 11-Module 01-Lesson 09_Clustering/23. Salary Range.html
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/11. Screencast Dummy Variables.html
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Part 05-Module 01-Lesson 05_Data Quality/18. Auditing Uniformity-cF0AEW4SIUM.en.vtt
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Video Aliases for Multiple Window Functions.html
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/20. Building the Linear Model.html
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Part 12-Module 01-Lesson 05_Interview Practice/08. Keep Practicing!.html
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/23. Video Interpreting Interactions.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-FC_GNjqj5zI.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/23. Measures of Center.html
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Part 12-Module 02-Lesson 08_Technical Interview - Python/Project Description - Technical Interview Practice.html
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/06. Cleaning Column Labels.html
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/20. 20. Which Distribution.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/06. Other Techniques.html
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Part 10-Module 01-Lesson 03_Udacity Professional Profile/07. Projects.html
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Part 13-Module 01-Lesson 04_Design Principles/index.html
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Part 17-Module 01-Lesson 14_Regression/04. Video Introduction to Linear Regression.html
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Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/18. Sensitivity and Robustness-T2QI3p0yDNk.ar.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/15. Different Bin Sizes.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/06. Flexible Schema.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-FC_GNjqj5zI.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/06. The Rise of Diamonds.html
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Part 11-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron.html
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Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2.html
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Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1.html
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Part 07-Module 01-Lesson 01_GitHub Review/17. Resources in Your Career Portal.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/09. Metric Choice.html
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/04. Consistency of Diversion-im8-LLU5J_Y.ar.vtt
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/16. Results with Merged Dataset.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/12. Iterating on Visualizations.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/03. Unit of Diversion Example-W4Xno_vJvZM.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/09. Operational Definition.html
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Part 18-Module 02-Lesson 01_Gathering Data/11. Flashforward 1.html
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/15. Video Potential Problems.html
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Part 17-Module 01-Lesson 11_Confidence Intervals/11. ScreenCast Traditional Confidence Interval Methods.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/09. Operational Definition.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/08. Data Visualization and You.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/25. Transition to Tech Portion.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/20. Duration vs. Exposure-MsByTo7FRgs.ar.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/28. Conclusion.html
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Part 03-Module 01-Lesson 20_L8 Estimation/01. Summary.html
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20.html
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/07. Solutions JOINs with Comparison Operators.html
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Part 19-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/09. The Data Science Process.html
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Part 09-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data.html
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Part 11-Module 01-Lesson 10_Feature Scaling/11. MinMax Scaler in sklearn-lgoh5R05YM0.ar.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/03. Example of Aggregation Framework-pOJAW4jTjr0.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5.html
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Part 03-Module 01-Lesson 08_L3 Central Tendency/31. Good Job!.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation.html
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Part 21-Module 01-Lesson 05_Scripting/29. Conclusion.html
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/16. 16. Population Distribution Shape.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/22. Scraping Solution.html
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/06. Matrix Multiplication Part 1-JRoCFQRP4B0.en.vtt
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Part 17-Module 01-Lesson 14_Regression/15. Screencast Fitting A Regression Line in Python.html
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Part 09-Module 01-Lesson 04_Problem Set Explore One Variable/02. Price Histogram.html
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/24. Final Thoughts.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/03. Intro to AB Testing-ASQubLvGuxY.pt-BR.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads.html
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Part 05-Module 02-Lesson 01_Data and Tables/08. Aggregations.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/01. Welcome!.html
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/23. McDonald's.html
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/09. The Facebook Offering.html
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Part 18-Module 02-Lesson 01_Gathering Data/19. Mashup Solution.html
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Part 17-Module 01-Lesson 14_Regression/22. Text Recap + Next Steps.html
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Part 17-Module 01-Lesson 04_Probability/20. Text Recap + Next Steps.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/23. McDonald's.html
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/24. 45. What Proportion.html
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Part 11-Module 01-Lesson 11_Text Learning/17. Warming Up with parseOutText().html
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Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads.html
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Part 14-Module 01-Lesson 05_Analyzing Results/15. Multiple Metrics Example 3.html
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/15. 15. Probability Decreased.html
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Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/05. 8. True or False.html
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/06. Matrix Multiplication Part 1-JRoCFQRP4B0.pt-BR.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2.html
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/05. Video POSITION, STRPOS, SUBSTR.html
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Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris.html
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Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head.html
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5.html
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/10. Solutions Self JOINs.html
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/26. Video Recap.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/19. Randomness.html
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/14. 18. Symbols = Fun Fun Fun!.html
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/Project Description - Craft Your Cover Letter.html
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula.html
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Part 21-Module 01-Lesson 04_Functions/04. Solution Defining Functions.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/28. Server Requests and D3-Lx9dhgMZO1s.en.vtt
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Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/01. SQL Scramble Top 10 Composers.html
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Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements.html
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/20. Type Quality Plot with Matplotlib.html
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/02. Video + Text What's Ahead.html
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/07. 9. Survey to Friends.html
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/08. Rankings of Visual Encodings.html
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Part 16-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example.html
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Part 07-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2.html
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Part 11-Module 01-Lesson 09_Clustering/10. K-Means Clustering Visualization 2.html
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/06. Video More On Subqueries.html
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Part 16-Module 02-Lesson 01_The Data Analysis Process/01. Handoff to Juno Lee.html
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/13. Solutions UNION.html
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Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables.html
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Part 19-Module 01-Lesson 02_Design/14. Designing for Color Blindness.html
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Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails.html
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/12. Data.html
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Part 04-Module 02-Lesson 01_Data Analysis Process/06. CSVs in Python-22sQCo6ovH0.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/12. Data.html
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Part 18-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate.html
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Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous.html
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Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-v4UGBUB6jO4.ar.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/23. Drawing Conclusions Example.html
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends.html
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Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6.html
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Part 09-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes.html
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Part 10-Module 01-Lesson 03_Udacity Professional Profile/04. Top Section.html
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Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4.html
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/15. Standardizing Each Column Again-WmJKPUthUPw.ar.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/15. Standardizing Each Column Again-WmJKPUthUPw.ar.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/05. Your Udacity Professional Profile.html
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Part 13-Module 01-Lesson 04_Design Principles/13. Additional Chart Types-4G-KhrIDqGA.ar.vtt
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Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/07. Promotional Music Event.html
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Part 11-Module 01-Lesson 08_Outliers/14. Enron Outliers.html
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Part 09-Module 01-Lesson 03_Explore One Variable/02. What to Do First.html
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Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/10. Heading to France.html
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Part 13-Module 01-Lesson 08_Animation and Interaction/49. The Future of Data Visualizations--CWbVBYBYWU.en.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial.html
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Part 16-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling and EDA.html
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Part 17-Module 01-Lesson 11_Confidence Intervals/07. Video Confidence Interval Applications.html
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Part 03-Module 01-Lesson 12_PS 4 Variability/06. 6. Udacians' Facebook Friends (mean +- std dev).html
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/10. Scatterplot Transformation.html
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Part 05-Module 02-Lesson 05_Deeper into SQL/03. Normalized Design Part Two.html
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Part 16-Module 03-Lesson 02_SQL Joins/18. Video JOINs and Filtering.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/15. Extracting Entities.html
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Part 06-Module 01-Lesson 03_Analyzing Data/18. Using Indexes-vL9FcO_9dCA.pt-BR.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results.html
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Part 09-Module 01-Lesson 07_Explore Many Variables/24. Many Variables.html
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Part 12-Module 02-Lesson 08_Technical Interview - Python/11. Time for Live Practice with Pramp.html
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Part 04-Module 01-Lesson 02_Jupyter notebooks/10. Creating a slideshow.html
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Part 16-Module 01-Lesson 02_Jupyter notebooks/10. Creating a slideshow.html
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability.html
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Part 16-Module 02-Lesson 01_The Data Analysis Process/20. Plotting with Pandas.html
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Part 17-Module 01-Lesson 13_Case Study AB tests/08. Click Through Rate.html
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Part 14-Module 01-Lesson 05_Analyzing Results/08. Single Metric Introduction.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/17. Sizing Example.html
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Part 16-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions.html
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/08. Solutions More On Subqueries.html
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Part 05-Module 01-Lesson 05_Data Quality/18. Auditing Uniformity-cF0AEW4SIUM.pt-BR.vtt
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/07. Resume Review (Prior Industry Experience).html
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Part 17-Module 01-Lesson 05_Binomial Distribution/17. Text Recap + Next Steps.html
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/04. David's Data Wrangling Example-TN-CWy3GK44.pt-BR.vtt
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/09. Fixing Data Types Pt 1.html
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Part 11-Module 01-Lesson 11_Text Learning/06. Bag of Words in Sklearn-aCdg-d_476Y.ar.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/19. Exists.html
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Part 21-Module 01-Lesson 04_Functions/16. [Optional] Solution Iterators and Generators.html
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Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/14. 28. Thinking About Distributions.html
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/04. David's Data Wrangling Example-TN-CWy3GK44.en.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data.html
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/06. Matrix Multiplication Part 1-JRoCFQRP4B0.zh-CN.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/01. Welcome!.html
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Part 11-Module 01-Lesson 11_Text Learning/18. Deploying Stemming.html
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction.html
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/09. Between 118 and 226.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose.html
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Part 03-Module 01-Lesson 07_Google Spreadsheet Tutorial/01. Tutorial-c3yK3OhuNvo.en-US.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/17. Question 5.html
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Part 03-Module 01-Lesson 12_PS 4 Variability/07. 7. Udacians' Facebook Friends (proportion).html
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Part 05-Module 02-Lesson 06_Problem Set Deeper Into SQL/12. Mystery Code.html
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/15. 32. Which Is Better.html
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Part 13-Module 01-Lesson 08_Animation and Interaction/index.html
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/15. Question 3.html
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Part 03-Module 01-Lesson 07_Google Spreadsheet Tutorial/01. Tutorial-c3yK3OhuNvo.en.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/09. Querying Using Field Selection.html
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Part 16-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion.html
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Part 13-Module 02-Lesson 01_Make Effective Data Visualization/Project Description - Make Effective Data Visualization.html
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/02. Data Overview.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/21. Querying Arrays Using Scalars.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/04. Consistency of Diversion.html
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/13. Solutions CAST.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Video Introduction to Window Functions.html
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Part 19-Module 01-Lesson 02_Design/16. General Design Tips.html
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/05. 6. Characteristic of a Population.html
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/27. 48. Depression.html
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Part 16-Module 03-Lesson 02_SQL Joins/03. Video Introduction to JOINs.html
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/06. 7. Sample Approximates Population.html
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value.html
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262.html
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value.html
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Part 17-Module 01-Lesson 14_Regression/01. Video Introduction.html
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Part 09-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/08. Unit of Analysis vs. Unit of Diversion.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Video Aggregates in Window Functions.html
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/19. 33. All Kinds of Variables.html
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Part 03-Module 01-Lesson 14_PS 5a Standardizing/14. 19. True or False.html
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/07. Resume Review (Career Change).html
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Part 11-Module 01-Lesson 14_Validation/18. Deploying a TrainingTesting Regime.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/15. Experiment Design and Sizing Overview.html
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/03. 2. Sleepy College Students.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/13. Getting Data into MongoDB.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/16. Beginning to Build Our http Requests.html
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/06. Quiz POSITION, STRPOS, SUBSTR - AME DATA AS QUIZ 1.html
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/02. 1. All California Residents.html
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/18. 18. Mean of Sampling Distribution.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/06. Ethical Considerations for Diversion.html
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/04. 3. Not Enough Sleep....html
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Part 19-Module 01-Lesson 02_Design/21. Recap.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/02. Data Modeling in MongoDB.html
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Part 11-Module 01-Lesson 07_Regressions/index.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Video Introduction to Percentiles.html
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather (CSV Files).html
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Part 12-Module 02-Lesson 02_List-Based Collections/12. Queue Practice.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/11. Multiple Field Queries.html
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/19. 19. SD of Sampling Distribution.html
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Part 07-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages.html
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Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/06. prop_initiated vs. tenure.html
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Part 11-Module 01-Lesson 08_Outliers/17. Any More Outliers.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/03. Intro to AB Testing-ASQubLvGuxY.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/02. Probability.html
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review.html
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/04. 4. Increase Sample Size.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/15. Who Has More Shoes.html
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/01. 1. Central Limit Theorem.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Video ROW_NUMBER RANK.html
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather (Intro).html
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/03. 3. Average Difference.html
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Part 05-Module 01-Lesson 05_Data Quality/08. Example Using our Blueprint-G3RjHqqQSgE.pt-BR.vtt
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Part 03-Module 01-Lesson 24_PS 9a Hypothesis Testing/01. 1. True or False.html
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/03. Types of Effect-Size Measures.html
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/07. Resume Review (Entry-level).html
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/25. Changing Bin Size.html
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/11. How Do I Find Time for My Nanodegree.html
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Part 11-Module 01-Lesson 10_Feature Scaling/17. When to Deploy Feature Scaling.html
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Part 18-Module 02-Lesson 01_Gathering Data/25. You Can Iterate.html
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/14. 14. Probability.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/12. Projection Queries.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/29. Removing Documents.html
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Video Recap.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/14. Population vs. Cohort Example.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/21. Duration vs. Exposure Example.html
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/05. 5. Standard Error.html
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/11. 11. Probability.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/03. XML Design Principles-eQpSC0IFhv0.ar.vtt
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Part 11-Module 01-Lesson 11_Text Learning/20. TfIdf It.html
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/11. Acne Medication.html
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/07. 7. n and x-bar.html
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion.html
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Part 12-Module 02-Lesson 08_Technical Interview - Python/08. Coding 2-qEteyPNRSwU.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/11. Report Results Effect Size.html
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/07. Univariate Plots.html
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/14. Types of Merges.html
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Part 18-Module 02-Lesson 01_Gathering Data/01. Introduction.html
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Part 03-Module 01-Lesson 29_PS 10b t-Tests, Part 2/11. 22. Cell Phone Law Decision.html
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/09. Solution Video More On Subqueries.html
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Part 18-Module 03-Lesson 01_Assessing Data/21. Assessing Summary.html
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/02. Data Has Dimensions-F4NSv776X0c.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/20. Three-Dimensional Data.html
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Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/04. Price vs. Volume and Diamond Clarity.html
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/07. Solutions POSITION, STRPOS, SUBSTR.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/02. Intro to XML.html
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/09. Using CSV Module--S4vc6tvxoI.en.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects.html
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/02. Linear Regression Models.html
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Part 05-Module 02-Lesson 01_Data and Tables/13. Uniqueness and Keys.html
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Part 03-Module 01-Lesson 12_PS 4 Variability/01. 1. Udacians' Facebook Friends (Mean).html
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Part 17-Module 01-Lesson 13_Case Study AB tests/09. Experiment II.html
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Part 11-Module 01-Lesson 09_Clustering/13. Some challenges of k-means.html
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Part 19-Module 01-Lesson 02_Design/08. Data Ink Ratio.html
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/19. Question 7.html
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Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/01. Price Histograms with Facet and Color.html
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Part 03-Module 01-Lesson 12_PS 4 Variability/04. 4. Udacians' Facebook Friends (Variance).html
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Part 03-Module 01-Lesson 12_PS 4 Variability/05. 5. Udacians' Facebook Friends (Std Dev).html
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/14. Question 2.html
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Part 17-Module 01-Lesson 14_Regression/21. Video Recap.html
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Part 11-Module 01-Lesson 09_Clustering/01. Unsupervised Learning.html
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/01. Lesson Overview.html
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Part 05-Module 02-Lesson 06_Problem Set Deeper Into SQL/07. DB API - Playground.html
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Part 11-Module 01-Lesson 08_Outliers/15. Identify the Biggest Enron Outlier.html
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Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-5571wc0iWCI.ar.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/13. Where's the Data.html
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Part 11-Module 02-Lesson 01_Identify Fraud from Enron Email/01. Project Overview.html
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Part 11-Module 01-Lesson 11_Text Learning/06. Bag of Words in Sklearn.html
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/16. Type Quality Plot - Part 1.html
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Part 07-Module 01-Lesson 01_GitHub Review/02. GitHub profile important items.html
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Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/10. Question 10.html
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Part 11-Module 01-Lesson 09_Clustering/02. Clustering Movies.html
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Part 17-Module 01-Lesson 11_Confidence Intervals/16. Video Confidence Intervals Hypothesis Tests.html
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/index.html
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Part 07-Module 01-Lesson 01_GitHub Review/01. Introduction.html
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Part 18-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty vs. Messy 1.html
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Part 03-Module 01-Lesson 13_L5 Standardizing/17. Z-Score.html
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Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/10. PriceCarat Binned, Faceted, Colored.html
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Part 15-Module 01-Lesson 02_Design Principles/12. Careful with Color.html
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Part 16-Module 03-Lesson 01_Basic SQL/index.html
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Part 03-Module 01-Lesson 13_L5 Standardizing/08. Infinitely Small.html
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Part 03-Module 01-Lesson 10_PS 3b Additional Practice (Optional)/07. 17. Deal or No Deal (Frequency).html
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Part 12-Module 02-Lesson 08_Technical Interview - Python/07. Coding-zhQYREUI8Z0.pt-BR.vtt
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Part 03-Module 01-Lesson 17_PS 6 Normal Distribution/15. 15. Meanings.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/12. Example Details.html
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Part 18-Module 03-Lesson 01_Assessing Data/12. Data Quality Dimensions 1-5UYGvKDsd-M.pt-BR.vtt
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Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/08. 21. Commute Time.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/11. Other Techniques Example-z1UX9i9_piQ.zh-CN.vtt
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Part 19-Module 01-Lesson 02_Design/18. Tell A Story.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/15. Calculating a Confidence Interval-HGYW-skXvY4.ar.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/03. Dataset Oral Insulin Clinical Trial Data-R-HT78SPxpE.en.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/03. Dataset Oral Insulin Clinical Trial Data -R-HT78SPxpE.en.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/12. Intro to JSON-Fi7RjhBLobY.ar.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/08. Video Self JOINs.html
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Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/15. A Tale of Four Quadrants.html
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Part 13-Module 01-Lesson 08_Animation and Interaction/05. Lets Make a Map-mOZuq2JoN-k.ar.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/01. About This Lesson.html
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Part 11-Module 01-Lesson 09_Clustering/17. Clustering Mini-Project Video.html
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Part 05-Module 02-Lesson 01_Data and Tables/07. Anatomy of a Table.html
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Part 18-Module 04-Lesson 01_Cleaning Data/20. Conclusion.html
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Part 16-Module 02-Lesson 01_The Data Analysis Process/17. Cleaning Example-7bnSPYtPDzQ.en.vtt
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Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/02. 8. Calculate Percentages.html
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Part 03-Module 01-Lesson 29_PS 10b t-Tests, Part 2/13. 24. Cell Phone Law CI.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/21. Best Practices for Scraping.html
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Part 21-Module 01-Lesson 04_Functions/01. Introduction.html
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Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/01. 3. t-Test.html
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/01. Problem Set Numbering.html
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/13. Karma.html
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/01. Video Communicating With Your Data.html
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Part 05-Module 02-Lesson 06_Problem Set Deeper Into SQL/03. WARM UP - JOIN to Subquery.html
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/02. Data Overview.html
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Part 11-Module 01-Lesson 02_Naive Bayes/01. ML in The Google Self-Driving Car-lL16AQItG1g.ar.vtt
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Part 11-Module 01-Lesson 09_Clustering/12. Sklearn.html
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Part 18-Module 03-Lesson 01_Assessing Data/07. Visual Assessment.html
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby.html
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Part 11-Module 01-Lesson 11_Text Learning/16. Text Learning Mini-Project.html
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Part 11-Module 01-Lesson 10_Feature Scaling/15. What Kind of Scaling.html
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Part 21-Module 01-Lesson 04_Functions/06. Variable Scope.html
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Part 17-Module 01-Lesson 13_Case Study AB tests/04. Business Example.html
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Part 21-Module 01-Lesson 02_Data Types and Operators/13. Strings-ySZDrs-nNqg.ar.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/05. Fundamentals of XML-Ti8K9FmNW1w.pt-BR.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/04. First Principle Risk.html
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Part 17-Module 01-Lesson 11_Confidence Intervals/01. Video Introduction.html
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Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/02. Price vs. Table Colored by Cut.html
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Part 09-Module 02-Lesson 01_Explore and Summarize Data/04. Evaluation and Submission.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/02. Metric Definition Overview-pOxyL1lwBIw.ar.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/08. Address Missing Data First.html
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Part 05-Module 02-Lesson 02_Problem Set Data and Tables/08. Schema Match.html
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/19. Plotting with Matplotlib.html
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Part 18-Module 03-Lesson 01_Assessing Data/12. Data Quality Dimensions 1-5UYGvKDsd-M.en.vtt
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Part 03-Module 01-Lesson 27_PS 10a t-Tests, Part 1/10. 10. Vocabularies - Mean and SD.html
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Part 03-Module 01-Lesson 10_PS 3b Additional Practice (Optional)/10. 23. Which Distributions.html
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Part 21-Module 01-Lesson 04_Functions/13. Solution Lambda Expressions.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/26. Empirical Confidence Intervals-ca8GQmr7B8g.ar.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/05. Fundamentals of XML.html
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Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/03. WARM UP - JOIN Artist to Album.html
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Part 09-Module 01-Lesson 02_R Basics/10. Read and Subset Data-UdniaeLsViQ.ja.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/03. Example of Aggregation Framework.html
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Part 03-Module 01-Lesson 13_L5 Standardizing/10. Theoretical Normal Distribution.html
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Part 11-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy.html
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Part 05-Module 02-Lesson 06_Problem Set Deeper Into SQL/01. WARM UP - Sum Top 5 Subquery.html
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/03. Video Hierarchies with Trina.html
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Part 11-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/23. The Facebook Offering-ORLP-phGXMU.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/25. Empirical Variability Sanity Checking-6vxdVWIA6dI.en.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/01. Video Motivation.html
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Part 05-Module 02-Lesson 03_Elements of SQL/04. Just a few SQL types.html
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Part 09-Module 01-Lesson 02_R Basics/15. Data Munging.html
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Part 06-Module 01-Lesson 03_Analyzing Data/08. Match Operator.html
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Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/04. Question 3.html
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Part 14-Module 02-Lesson 01_Design an AB Test/01. Project Overview and Details.html
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Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes.html
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Part 11-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video.html
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Part 03-Module 01-Lesson 13_L5 Standardizing/21. Standard Normal Distribution.html
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Part 07-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2.html
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Part 13-Module 01-Lesson 08_Animation and Interaction/46. World Cup Code and Narrative Recap-lnHEvGeech0.ar.vtt
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Part 03-Module 01-Lesson 09_PS 3a Central Tendency/03. 3. BBC Memory Scores.html
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Part 18-Module 03-Lesson 01_Assessing Data/09. Quality Visual Assessment 1 -XfKc5PtJ7cc.pt-BR.vtt
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Part 09-Module 01-Lesson 02_R Basics/09. Getting Help.html
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Part 06-Module 01-Lesson 03_Analyzing Data/09. Project Operator-_kupbxrZBds.pt-BR.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/img/resid-plots.gif
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/04. Meet the Careers Team.html
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Part 11-Module 01-Lesson 02_Naive Bayes/18. Gaussian NB Example-wpnDwiqTCJA.ar.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/03. Dataset Oral Insulin Clinical Trial Data-R-HT78SPxpE.pt-BR.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/03. Dataset Oral Insulin Clinical Trial Data -R-HT78SPxpE.pt-BR.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/18. Using Indexes.html
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Part 12-Module 01-Lesson 05_Interview Practice/09. Resources in Your Career Portal.html
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/01. Data Visualization Introduction.html
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Part 06-Module 01-Lesson 03_Analyzing Data/13. Group Accumulation Operators.html
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Part 11-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning.html
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/07. Loading Data into a DataFrame.html
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/07. Loading Data into a DataFrame.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/13. Metric Definition Example-xOSypbjALh4.zh-CN.vtt
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Part 05-Module 02-Lesson 06_Problem Set Deeper Into SQL/10. Local Query - Below Average Song Lengths.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/10. Intro to Screen Scraping.html
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Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/07. Correlation - price and depth.html
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Part 11-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/05. Refining the Customer Funnel-L2NEk4jvlcY.en.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/05. NumPy and Pandas Data Types.html
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/19. More Tableau Practice.html
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/05. NumPy and Pandas Data Types.html
7.2 kB
Part 03-Module 01-Lesson 17_PS 6 Normal Distribution/13. 13. Less than -2.33.html
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Part 07-Module 01-Lesson 01_GitHub Review/16. Outro.html
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Part 09-Module 01-Lesson 01_What is EDA/02. Go Exploring.html
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Part 04-Module 01-Lesson 01_Anaconda/06. More environment actions.html
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Part 16-Module 01-Lesson 01_Anaconda/06. More environment actions.html
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Part 03-Module 01-Lesson 07_Google Spreadsheet Tutorial/01. Tutorial-c3yK3OhuNvo.zh-CN.vtt
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Part 11-Module 01-Lesson 11_Text Learning/14. Why Upweight Rare Words.html
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Part 17-Module 01-Lesson 06_Conditional Probability/16. Text Summary.html
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Part 11-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project.html
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Part 03-Module 01-Lesson 13_L5 Standardizing/02. USCF Distribution.html
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/14. Video COALESCE.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/28. Server Requests and D3-Lx9dhgMZO1s.zh-CN.vtt
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/22. CHALLENGE 22. What Sample Size.html
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/08. Resources in Your Career Portal.html
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Part 11-Module 01-Lesson 13_PCA/28. PCA in sklearn-SBYdqlLgbGk.ar.vtt
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Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/01. Data Visualization Resources.html
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Part 03-Module 01-Lesson 10_PS 3b Additional Practice (Optional)/09. 19. Deal or No Deal (Center).html
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Part 18-Module 04-Lesson 01_Cleaning Data/10. Solution Missing Data.html
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/07. Matrix Multiplication Part 2.html
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Part 09-Module 01-Lesson 02_R Basics/10. Read and Subset Data.html
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Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/11. Correlations on Subsets.html
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Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/17. 31. Skewness.html
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/01. Video Introduction to SQL Data Cleaning.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/01. Welcome to Lesson 2.html
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Part 18-Module 04-Lesson 01_Cleaning Data/06. Cleaning Sequences.html
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Part 18-Module 04-Lesson 01_Cleaning Data/09. Quiz Missing Data.html
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Part 18-Module 04-Lesson 01_Cleaning Data/13. Solution Tidiness.html
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Part 18-Module 04-Lesson 01_Cleaning Data/16. Solution Quality.html
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/06. Write the Conclusion.html
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/14. Video Performance Tuning Motivation.html
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Part 07-Module 01-Lesson 01_GitHub Review/04. Interview with Art - Part 1.html
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Part 07-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2.html
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Part 07-Module 01-Lesson 01_GitHub Review/13. Interview with Art - Part 3.html
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Part 03-Module 01-Lesson 09_PS 3a Central Tendency/09. 9. Median.html
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Part 18-Module 04-Lesson 01_Cleaning Data/12. Quiz Tidiness.html
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Part 18-Module 02-Lesson 01_Gathering Data/11. Flashforward 1-Sr5v0i9m_sw.ar.vtt
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Part 03-Module 01-Lesson 09_PS 3a Central Tendency/10. 10. Mode.html
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Part 18-Module 04-Lesson 01_Cleaning Data/15. Quiz Quality.html
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/01. Video Introduction to Advanced SQL.html
7.2 kB
Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/07. Smoothing prop_initiated vs. tenure.html
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Part 11-Module 01-Lesson 14_Validation/15. Validation Mini-Project Video.html
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/01. Video What is Tableau.html
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/08. 8. Mean of Sample Means.html
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Part 03-Module 01-Lesson 09_PS 3a Central Tendency/08. 8. Mean.html
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Part 11-Module 01-Lesson 11_Text Learning/11. Stemming with NLTK.html
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Part 05-Module 02-Lesson 05_Deeper into SQL/02. Normalized Design Part One.html
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/10. Summary of Principles.html
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/13. Series Indexes-RK6CPtXdK5Q.ar.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/14. Series Indexes-RK6CPtXdK5Q.ar.vtt
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Part 14-Module 01-Lesson 06_Final Project/01. Project Instructions.html
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/02. Video Introduction to Subqueries.html
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Part 11-Module 01-Lesson 08_Outliers/11. Score of Regression with Outliers.html
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Part 03-Module 01-Lesson 10_PS 3b Additional Practice (Optional)/04. 14. Deal or No Deal (Mean vs. Median).html
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/02. Action Time.html
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/13. 13. Standard Error.html
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Part 05-Module 02-Lesson 05_Deeper into SQL/14. Writing Code with DB API.html
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/09. 9. Standard Error.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/04. XML in Practice.html
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Part 11-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm.html
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/12. 12. Mean n = 25.html
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/16. Pandas groupby()-smBMJlpWdVI.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/16. Pandas groupby()-smBMJlpWdVI.pt-BR.vtt
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Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/07. Question 6.html
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Part 03-Module 01-Lesson 13_L5 Standardizing/12. Unpopular.html
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/08. Calculating Correlation-isBv5D88Nso.ar.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/18. Visual Encodings-14FJU1kP6-M.ar.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/07. Visual Encodings - Data Visualization and D3.js-14FJU1kP6-M.ar.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/08. Calculating Correlation-isBv5D88Nso.ar.vtt
7.2 kB
Part 07-Module 01-Lesson 01_GitHub Review/03. Good GitHub repository.html
7.2 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/05. Fundamentals of XML-Ti8K9FmNW1w.en.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/05. Fundamentals of XML-Ti8K9FmNW1w.en-US.vtt
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/10. 10. Z-Score.html
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/09. Pandas Axis Names.html
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Part 09-Module 01-Lesson 02_R Basics/04. Install RStudio on Windows.html
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Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-4GBJk6R0pb4.ar.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/09. Pandas Axis Names.html
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Part 18-Module 04-Lesson 01_Cleaning Data/19. Cleaning Summary.html
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/17. Why Data Dashboards.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/27. Set Unset-bgOky14w77Q.ar.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/01. Introduction.html
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Part 09-Module 01-Lesson 02_R Basics/12. Factor Variables.html
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Part 19-Module 01-Lesson 02_Design/01. Introduction.html
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Part 03-Module 01-Lesson 17_PS 6 Normal Distribution/12. 12. Greater than 1.64.html
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/17. Type Quality Plot - Part 2.html
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Part 11-Module 01-Lesson 08_Outliers/13. Score After Cleaning.html
7.1 kB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/13. Question 1.html
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Part 03-Module 01-Lesson 29_PS 10b t-Tests, Part 2/03. 14. Cell Phone Law Independent Variable.html
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/08. Resources in Your Career Portal.html
7.1 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/16. Video Performance Tuning 2.html
7.1 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/17. Video Performance Tuning 3.html
7.1 kB
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/01. Communicating With Your Data.html
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Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/02. WARM UP - Query for Song Length.html
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Part 03-Module 01-Lesson 29_PS 10b t-Tests, Part 2/02. 13. Cell Phone Law Dependent Variable.html
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Part 04-Module 01-Lesson 01_Anaconda/08. On Python versions at Udacity.html
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Part 16-Module 01-Lesson 01_Anaconda/08. On Python versions at Udacity.html
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Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/01. 7. Ode to n.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/14. Procedure.html
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Part 11-Module 01-Lesson 01_Welcome to Machine Learning/01. Introduction-ICKBWIkfeJ8.ar.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/19. Video SQL Completion Congratulations.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-FC_GNjqj5zI.zh-CN.vtt
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Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/09. Question 9.html
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/08. Resources in Your Career Portal.html
7.1 kB
Part 06-Module 01-Lesson 03_Analyzing Data/09. Project Operator.html
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next.html
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Part 04-Module 01-Lesson 02_Jupyter notebooks/09. Converting notebooks.html
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Part 16-Module 01-Lesson 02_Jupyter notebooks/09. Converting notebooks.html
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/01. Introduction.html
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Part 11-Module 01-Lesson 08_Outliers/08. Outliers Mini-Project Video.html
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Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/01. Data Visualization Resources-OYl-saB2vWE.zh-CN.vtt
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/08. Video CONCAT.html
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/01. Introduction.html
7.1 kB
Part 03-Module 01-Lesson 29_PS 10b t-Tests, Part 2/01. 12. Cell Phone Law Type of Study.html
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/index.html
7.1 kB
Part 11-Module 01-Lesson 10_Feature Scaling/06. Comparing Features with Different Scales.html
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/23. Outro.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/23. Wrap-Up.html
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Part 21-Module 01-Lesson 02_Data Types and Operators/index.html
7.1 kB
Part 03-Module 01-Lesson 13_L5 Standardizing/11. Z.html
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Part 19-Module 01-Lesson 02_Design/22. Onwards!.html
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Part 05-Module 02-Lesson 06_Problem Set Deeper Into SQL/02. WARM UP - Invoice Above Average.html
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Part 17-Module 01-Lesson 13_Case Study AB tests/14. Analyzing Multiple Metrics.html
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Part 18-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 Solution-E5tAoCK6GcQ.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/30. Lessons Learned, Part 2-1JRk6dgQhkE.en.vtt
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/18. Table Calculations.html
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Part 05-Module 02-Lesson 02_Problem Set Data and Tables/07. Missing Tables.html
7.1 kB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/02. Heads Up.html
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Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/05. 5. Guesstimate.html
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Part 06-Module 01-Lesson 03_Analyzing Data/09. Project Operator-_kupbxrZBds.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/13. Binomial Distribution-nXbucNJpP8I.en.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/06. Quick Fixes #1.html
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Part 13-Module 01-Lesson 04_Design Principles/06. Common Chart Types-xD2_AU6atqA.ar.vtt
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Part 15-Module 01-Lesson 02_Design Principles/02. Tipos Comuns de Gráficos-xD2_AU6atqA.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/23. Learning Effects-nFpIDWPUDm8.pt-BR.vtt
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Part 05-Module 01-Lesson 05_Data Quality/14. Auditing Accuracy 2.html
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Part 05-Module 01-Lesson 05_Data Quality/18. Auditing Uniformity.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/07. Parsing XML-SIsG0HYYwY4.zh-CN.vtt
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Part 10-Module 01-Lesson 03_Udacity Professional Profile/09. Resources in Your Career Portal.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/08. Intro to PyMongo-h6M4x9aXx5g.ar.vtt
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Part 11-Module 01-Lesson 08_Outliers/09. Outliers Mini-Project.html
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Part 11-Module 01-Lesson 10_Feature Scaling/13. Feature Scaling Mini-Project Video.html
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Part 09-Module 01-Lesson 04_Problem Set Explore One Variable/04. Diamond Counts.html
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Part 18-Module 02-Lesson 01_Gathering Data/10. HTML Files In Python 2-3caDGTxcoCw.en.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/03. Dataset Oral Insulin Clinical Trial Data-R-HT78SPxpE.zh-CN.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/03. Dataset Oral Insulin Clinical Trial Data -R-HT78SPxpE.zh-CN.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/21. Great Job!.html
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Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/03. Correlations.html
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Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/03. Typical Table Value.html
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Part 11-Module 01-Lesson 13_PCA/index.html
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Part 16-Module 02-Lesson 01_The Data Analysis Process/17. Cleaning Example-7bnSPYtPDzQ.zh-CN.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/07. Sanity Checking Wrapup.html
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Part 09-Module 02-Lesson 01_Explore and Summarize Data/05. Example Project.html
7.1 kB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/08. Resources in Your Career Portal.html
7.0 kB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/01. Data Visualization Introduction.html
7.0 kB
Part 14-Module 01-Lesson 05_Analyzing Results/10. Single Metric Gotchas.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/30. Lessons Learned, Part 2-1JRk6dgQhkE.pt-BR.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/04. David's Data Wrangling Example-TN-CWy3GK44.zh-CN.vtt
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Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/04. 4. Type A.html
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Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/06. 14. Independent Variable.html
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Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/12. 25. Frequency and Bin Size.html
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Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/11. 17. Which Region.html
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/08. Auditing Street Names-c0IcUiF_kXs.ar.vtt
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/09. Auditing Street Names-c0IcUiF_kXs.ar.vtt
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Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-TIgfjmp-4BA.ar.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2-ZXy8jgywY5g.ar.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/18. Conclusion.html
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Part 12-Module 02-Lesson 05_Trees/05. Tree Traversal.html
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Part 12-Module 02-Lesson 05_Trees/20. Tree Rotations.html
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/02. Familiarize Yourself with the Dataset.html
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/06. Resume Review.html
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Part 05-Module 02-Lesson 05_Deeper into SQL/05. CREATE TABLE and Types.html
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/12. Final Tips.html
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/Project Description - Resume Review Project (Career Change).html
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Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-O9d9dKyHtIc.ar.vtt
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Part 05-Module 01-Lesson 06_Problem Set Data Quality/07. SQL or MongoDB.html
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Part 03-Module 01-Lesson 09_PS 3a Central Tendency/01. 1. BBC Memory Scores.html
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Part 03-Module 01-Lesson 09_PS 3a Central Tendency/04. 4. What Distribution.html
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Part 05-Module 02-Lesson 05_Deeper into SQL/19. Outro.html
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/index.html
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Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/11. Stay Curious!.html
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Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/04. 6. P-Value.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/14. Filtering and Segmenting-DETCNMqnnKw.pt-BR.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/10. HTML Files in Python 1-0VZumC18UvQ.zh-CN.vtt
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Part 12-Module 02-Lesson 05_Trees/02. Tree Basics.html
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/08. Support from the Udacity Team.html
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Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/14. 22. Percent of Variability.html
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Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/03. 5. P-Value.html
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Part 05-Module 02-Lesson 05_Deeper into SQL/12. What's a DB-API.html
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Part 13-Module 01-Lesson 08_Animation and Interaction/49. The Future of Data Visualizations--CWbVBYBYWU.zh-CN.vtt
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Part 03-Module 01-Lesson 09_PS 3a Central Tendency/05. 5. What Distribution.html
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/03. Assessing the Quality of Data Pt. 1.html
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/04. Assessing the Quality of Data Pt. 2.html
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Part 03-Module 01-Lesson 27_PS 10a t-Tests, Part 1/07. 7. Vocabularies - Alternative Hypothesis.html
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Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/02. 4. t-Critical Value.html
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/05. Iterating through Ways Tags-GYhOEJ8EXkg.ar.vtt
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/06. Iterating through Ways Tags-GYhOEJ8EXkg.ar.vtt
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Part 11-Module 01-Lesson 09_Clustering/12. Sklearn-3zHUAXcoZ7c.pt-BR.vtt
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Part 03-Module 01-Lesson 32_PS 11b Additional Practice (Optional)/02. 2. t-Test.html
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Part 09-Module 01-Lesson 02_R Basics/10. Read and Subset Data-UdniaeLsViQ.en.vtt
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Part 03-Module 01-Lesson 17_PS 6 Normal Distribution/10. 10. Between 80 and 95.html
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Part 18-Module 02-Lesson 01_Gathering Data/10. HTML Files In Python 2-3caDGTxcoCw.pt-BR.vtt
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Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/08. 14. When Most Were Born.html
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Part 03-Module 01-Lesson 17_PS 6 Normal Distribution/09. 9. Between 65 and 90.html
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Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/03. Question 2.html
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Part 04-Module 02-Lesson 01_Data Analysis Process/17. Exploring Student Engagement-6QLiscx_zIY.en.vtt
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Part 03-Module 01-Lesson 17_PS 6 Normal Distribution/07. 7. Greater than 108.html
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Part 11-Module 01-Lesson 10_Feature Scaling/14. Feature Scaling Mini-Project.html
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Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/14. 26. Positively Skewed.html
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Part 03-Module 01-Lesson 27_PS 10a t-Tests, Part 1/06. 6. Vocabularies - Null Hypothesis.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/05. Fundamentals of XML-Ti8K9FmNW1w.zh-CN.vtt
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Part 09-Module 01-Lesson 02_R Basics/03. Using Windows.html
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Part 12-Module 02-Lesson 05_Trees/09. Insert.html
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Part 17-Module 01-Lesson 03_Admissions Case Study/12. Text Recap + Next Steps.html
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Part 03-Module 01-Lesson 17_PS 6 Normal Distribution/08. 8. Less than 76.html
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Part 12-Module 02-Lesson 05_Trees/01. Trees.html
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Part 03-Module 01-Lesson 14_PS 5a Standardizing/02. 2. Z-Scores.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/03. Metric Definition Overview, Part 2-0DyLzS2ux7g.en.vtt
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Part 12-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability-Zyq0FQ0XO3o.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/17. Exploring Student Engagement-6QLiscx_zIY.pt-BR.vtt
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Part 03-Module 01-Lesson 17_PS 6 Normal Distribution/11. 11. Top 30.html
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Part 05-Module 02-Lesson 02_Problem Set Data and Tables/11. Stay Curious!.html
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Part 12-Module 02-Lesson 05_Trees/12. BSTs.html
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Part 10-Module 01-Lesson 03_Udacity Professional Profile/02. Getting Started.html
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Part 13-Module 01-Lesson 07_Narrative Structures/25. Demystifying D3-y7QK8XMHyDQ.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/32. Enter Update Exit-0SU3cKsWsPw.en.vtt
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/09. Video Extra Practice with Dashboards.html
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Part 03-Module 01-Lesson 17_PS 6 Normal Distribution/03. 3. Houses.html
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Part 03-Module 01-Lesson 17_PS 6 Normal Distribution/04. 4. Houses.html
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Part 03-Module 01-Lesson 17_PS 6 Normal Distribution/06. 6. Houses.html
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/06. Resume Review.html
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Part 05-Module 02-Lesson 05_Deeper into SQL/16. Subqueries.html
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Part 14-Module 01-Lesson 05_Analyzing Results/06. Checking Invariants, Part 2-05jVh4kUbHU.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/01. Intro to SQL for Data Analysis.html
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Part 11-Module 01-Lesson 06_Datasets and Questions/04. Downloading Enron Data-TgkBAtaTqJk.pt-BR.vtt
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Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/12. Question 12.html
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/06. Resume Review.html
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Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/13. 21. Cohen's d.html
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/08. Auditing Street Names.html
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Part 21-Module 01-Lesson 01_Why Python Programming/04. Course Overview.html
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Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/12. 20. Decision.html
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Part 12-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question.html
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Part 21-Module 01-Lesson 03_Control Flow/index.html
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/05. Ways in the Open Street Map XML.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/03. Unit of Diversion Example-W4Xno_vJvZM.zh-CN.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/01. Interview Introduction.html
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/04. NumPy Arrays-UG924zKZF7U.pt-BR.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/05. NumPy Arrays-UG924zKZF7U.pt-BR.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/15. Filtering and Segmenting Example-WgM3cBEtkqg.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/24. Empirical Variability-Wzs1KFldiUE.en.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/01. Introduction to Conditional Probability.html
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Part 10-Module 01-Lesson 03_Udacity Professional Profile/01. Introduction.html
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Part 03-Module 01-Lesson 11_L4 Variability/index.html
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/02. Why Study a New Algorithm Solo.html
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/07. Connecting with Your Community.html
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Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/13. Scott's Advice to Break into Data Vis.html
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Part 12-Module 01-Lesson 01_Ace Your Interview/03. STAR Method.html
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Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-0L3Obq4FSVQ.ar.vtt
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Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/09. Largest Group Mean prop_initiated.html
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Part 12-Module 02-Lesson 03_Searching and Sorting/11. Efficiency of Merge Sort-HKiK5Y-YSkk.pt-BR.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/13. Data Modeling in JSON.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/03. Metric Definition Overview, Part 2-0DyLzS2ux7g.pt-BR.vtt
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/17. Conclusion.html
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Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/10. Findings - price vs. volume.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/15. Filtering and Segmenting Example-XTS6m5_3fdU.en.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/03. Confirming Inputs.html
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Part 05-Module 02-Lesson 02_Problem Set Data and Tables/06. Checking Setup.html
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Part 11-Module 01-Lesson 12_Feature Selection/index.html
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Part 05-Module 02-Lesson 03_Elements of SQL/10. Why Do It in the Database.html
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/01. Intro.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/26. Adding and Formatting China's Red Dot-qgTSR_ggTDg.en-US.vtt
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Part 09-Module 01-Lesson 04_Problem Set Explore One Variable/03. Price Histogram Summary.html
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Part 12-Module 02-Lesson 08_Technical Interview - Python/06. Runtime Analysis.html
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Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/02. Findings - price vs. x.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/26. Adding and Formatting China's Red Dot-qgTSR_ggTDg.en.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/01. Introduction.html
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Part 03-Module 01-Lesson 29_PS 10b t-Tests, Part 2/09. 20. Cell Phone Law Standard Error.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/16. Summary Metrics-ghMD3AfjLZc.pt-BR.vtt
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Part 03-Module 01-Lesson 15_PS 5b Additional Practice (Optional)/05. 18. Farthest from Mean.html
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Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/15. Trends in Mean Price.html
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Part 03-Module 01-Lesson 29_PS 10b t-Tests, Part 2/10. 21. Cell Phone Law t-Statistic.html
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Part 03-Module 01-Lesson 29_PS 10b t-Tests, Part 2/12. 23. Cell Phone Law Cohen's d.html
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences.html
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Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/04. Question 4.html
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/01. Get an Interview with a Cover Letter!.html
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Part 05-Module 02-Lesson 03_Elements of SQL/03. Types in the SQL World.html
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Part 14-Module 01-Lesson 05_Analyzing Results/16. Analyzing Multiple Metrics-mbHnQ_EdrZ8.pt-BR.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/index.html
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Part 12-Module 02-Lesson 08_Technical Interview - Python/05. Brainstorming.html
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Part 15-Module 01-Lesson 04_Telling Stories with Tableau/08. Further Learning.html
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Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet -K-Owid_mf8o.ar.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/05. Tabular Formats.html
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Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Part II-1GRv1S6K8gQ.ar.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/19. Lessons Completed in First Week -nZq-Y2lfjpY.pt-BR.vtt
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Part 10-Module 01-Lesson 02_LinkedIn Review/Project Description - LinkedIn Profile Review Project.html
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Part 12-Module 01-Lesson 02_Practice Behavioral Questions/04. Time When You Showed Initiative.html
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Part 11-Module 01-Lesson 01_Welcome to Machine Learning/01. Introduction-ICKBWIkfeJ8.ja.vtt
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/12. Video Congratulations!.html
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Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/13. Question 12.html
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Part 03-Module 01-Lesson 32_PS 11b Additional Practice (Optional)/01. 1. t-Test.html
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Part 05-Module 02-Lesson 01_Data and Tables/10. How Queries Happen.html
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/04. Meet Chris-0ccflD9x5WU.ar.vtt
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Part 12-Module 01-Lesson 02_Practice Behavioral Questions/03. Analyzing Behavioral Answers.html
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Part 15-Module 01-Lesson 02_Design Principles/img/diverging1.png
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Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/11. 19. t-Statistic.html
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/12. Intro to JSON.html
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/17. Check You Out.html
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Part 04-Module 02-Lesson 01_Data Analysis Process/03. Data Analysis Process-cAceF0h4vpI.ar.vtt
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Part 08-Module 01-Lesson 01_Conduct a Job Search/05. Resources in Your Career Portal.html
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Part 12-Module 02-Lesson 05_Trees/13. BST Complications.html
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/09. Questions and Consent.html
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Part 12-Module 02-Lesson 08_Technical Interview - Python/04. Test Cases.html
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Part 05-Module 01-Lesson 05_Data Quality/10. Wikipedia Infobox Dataset-hpyNAYJODqw.pt-BR.vtt
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assets/css/fonts/KaTeX_Size4-Regular.woff
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Part 03-Module 01-Lesson 27_PS 10a t-Tests, Part 1/09. 9. Vocabularies - t-Critical Value.html
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Part 03-Module 01-Lesson 14_PS 5a Standardizing/01. 1. Which Distribution Is Which.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/12. Metric Definition and Data Capture-qtVm_stSHuM.zh-CN.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/09. Debugging.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/index.html
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Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-Zdl01HMSjTw.ar.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/29. 11 CASE V2-BInXuTY_FzE.ar.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/16. Binomial Conclusion.html
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Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/09. 17. Degrees of Freedom.html
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Part 06-Module 01-Lesson 03_Analyzing Data/13. Group Accumulation Operators-cleAY1-Jboc.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/index.html
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Part 12-Module 02-Lesson 01_Introduction and Efficiency/10. Worst Case and Approximation.html
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Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/12. Question 11.html
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/09. Auditing Street Names.html
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Part 11-Module 01-Lesson 06_Datasets and Questions/04. Downloading Enron Data-TgkBAtaTqJk.en.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/07. Coding.html
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Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/02. Question 1.html
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Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/07. 13. Most Common Bin.html
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Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/04. 10. How Old.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/09. Metric Choice-BeIy4A6YKrY.ar.vtt
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Part 12-Module 01-Lesson 02_Practice Behavioral Questions/05. What Motivates You at the Workplace.html
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Part 12-Module 01-Lesson 02_Practice Behavioral Questions/08. Time When You Dealt With Failure.html
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Part 11-Module 01-Lesson 07_Regressions/31. R Squared in SKlearn-Dxf1I4IE6co.ar.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/13. Group Accumulation Operators-cleAY1-Jboc.en.vtt
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Part 12-Module 01-Lesson 03_Interview Fails/04. Interviewing Fails Lyla Fujiwara-CgK2HxdJzc8.en.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/02. Efficiency of Binary Search.html
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Part 03-Module 01-Lesson 27_PS 10a t-Tests, Part 1/08. 8. Vocabularies - One- or Two-Tailed.html
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Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/10. 18. t-Critical Values.html
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/04. Describe Your Work Experiences.html
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Part 10-Module 01-Lesson 02_LinkedIn Review/02. Resources in Your Career Portal.html
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Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/13. 20. How to Analyze Shape.html
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Part 06-Module 01-Lesson 03_Analyzing Data/18. Using Indexes-vL9FcO_9dCA.zh-CN.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/08. Efficiency of Bubble Sort.html
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Part 11-Module 01-Lesson 13_PCA/31. Eigenfaces Code-LgLYw-G4sLQ.en.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/10. HTML Files in Python 1-0VZumC18UvQ.pt-BR.vtt
6.4 kB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/04. Describe Your Work Experiences.html
6.4 kB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/07. What Do You Know About the Company.html
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/09. Using CSV Module--S4vc6tvxoI.zh-CN.vtt
6.4 kB
Part 12-Module 02-Lesson 03_Searching and Sorting/11. Efficiency of Merge Sort.html
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Part 12-Module 02-Lesson 03_Searching and Sorting/14. Efficiency of Quick Sort.html
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Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/10. 16. Heights of Bars.html
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Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/14. What is plot.ly.html
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Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/12. 19. How to Find n.html
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/index.html
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Part 05-Module 02-Lesson 01_Data and Tables/17. Summary.html
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Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/09. 15. Type of Data.html
6.4 kB
Part 03-Module 01-Lesson 21_PS 8a Estimation/01. 1. Point Estimates.html
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Part 14-Module 01-Lesson 05_Analyzing Results/09. Single Metric Example--QwMdwqUq9c.en.vtt
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Part 09-Module 01-Lesson 01_What is EDA/05. Goals of EDA.html
6.4 kB
Part 17-Module 01-Lesson 16_Logistic Regression/29. Model Diagnostics In Python-1Z4eorbfOOc.pt-BR.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/15. Conclusion.html
6.4 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/index.html
6.4 kB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary.html
6.4 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/index.html
6.4 kB
Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/16. Tips for Clarity AND Beauty.html
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Part 05-Module 02-Lesson 06_Problem Set Deeper Into SQL/06. Import CSV.html
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Part 11-Module 01-Lesson 02_Naive Bayes/01. ML in The Google Self-Driving Car-lL16AQItG1g.ja.vtt
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Part 13-Module 01-Lesson 04_Design Principles/13. Additional Chart Types-4G-KhrIDqGA.pt-BR.vtt
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Part 14-Module 01-Lesson 06_Final Project/06. Choosing Duration and Exposure.html
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Part 10-Module 01-Lesson 03_Udacity Professional Profile/06. Skills.html
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Part 14-Module 01-Lesson 05_Analyzing Results/03. Choosing Invariants-E1ePfjcVH3I.ar.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/06. Zoo.html
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Part 21-Module 01-Lesson 03_Control Flow/10. For Loops-UtX0PXSUCdY.zh-CN.vtt
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Part 03-Module 01-Lesson 22_PS 8b Additional Practice (Optional)/07. 17. Interpret CI.html
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/20. Notation for Random Variables-8NxTW1u4s-Y.ar.vtt
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/05. Iterating through Ways Tags.html
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Part 21-Module 01-Lesson 05_Scripting/20. Importing Files-qjeSn6zZbR0.zh-CN.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/06. Intro to Sorting.html
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Part 03-Module 01-Lesson 27_PS 10a t-Tests, Part 1/01. 1. Normal vs. t-Distribution.html
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Part 05-Module 01-Lesson 05_Data Quality/11. Auditing a Cross-Field Constraint-Y7TNXALXut8.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer.html
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/06. Wrapping Up.html
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Part 21-Module 01-Lesson 05_Scripting/06. Programming Environment Setup-EKxDnCK0NAk.ar.vtt
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Part 12-Module 02-Lesson 01_Introduction and Efficiency/08. Notation Intro.html
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Part 17-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/24. Empirical Variability-Wzs1KFldiUE.pt-BR.vtt
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Part 09-Module 01-Lesson 01_What is EDA/07. Our Approach for This Course.html
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/09. How Does Project Submission Work.html
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Part 03-Module 01-Lesson 14_PS 5a Standardizing/08. 11. Grade on a Curve.html
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Part 12-Module 02-Lesson 03_Searching and Sorting/01. Binary Search.html
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Part 03-Module 01-Lesson 24_PS 9a Hypothesis Testing/03. 3. Alternative Hypothesis.html
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Part 12-Module 01-Lesson 05_Interview Practice/01. Analyzing an Interview.html
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/13. You're Ready for the Project!.html
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Part 05-Module 01-Lesson 06_Problem Set Data Quality/04. Other Fields.html
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Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/05. Question 4.html
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Part 17-Module 01-Lesson 07_Bayes Rule/index.html
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/04. NumPy Arrays-UG924zKZF7U.en.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/index.html
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/05. NumPy Arrays-UG924zKZF7U.en.vtt
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Part 03-Module 02-Lesson 01_Test a Perceptual Phenomenon/02. Project Details.html
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/15. Summary.html
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Part 12-Module 02-Lesson 03_Searching and Sorting/07. Bubble Sort.html
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Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/07. Question 7.html
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Part 05-Module 01-Lesson 05_Data Quality/14. Auditing Accuracy 2-5xY3sCBHkOk.pt-BR.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/17. Summary Metrics Example--DqU-ARfQr4.ar.vtt
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Part 03-Module 01-Lesson 24_PS 9a Hypothesis Testing/02. 2. Null Hypothesis.html
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Part 13-Module 01-Lesson 04_Design Principles/13. Additional Chart Types-4G-KhrIDqGA.en.vtt
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Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules-jPGyFgcIvsM.ar.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/10. Merge Sort.html
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Part 12-Module 02-Lesson 03_Searching and Sorting/13. Quick Sort.html
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Part 13-Module 01-Lesson 08_Animation and Interaction/32. Enter Update Exit-0SU3cKsWsPw.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/03. XML Design Principles-eQpSC0IFhv0.pt-BR.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/04. Recursion.html
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Part 03-Module 01-Lesson 25_PS 9b Additional Practice (Optional)/03. 12. Z-Score.html
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Part 05-Module 02-Lesson 03_Elements of SQL/16. Wrap Up.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/05. Refining the Customer Funnel-L2NEk4jvlcY.zh-CN.vtt
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Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/06. 12. Birth Year Histogram.html
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Part 03-Module 01-Lesson 15_PS 5b Additional Practice (Optional)/04. 14. SJSU Football.html
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Part 03-Module 01-Lesson 15_PS 5b Additional Practice (Optional)/02. 8. IQ 125.html
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely.html
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (After Cleaning)-OF2486euiRE.pt-BR.vtt
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Part 03-Module 01-Lesson 17_PS 6 Normal Distribution/01. 1. Heights.html
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/09. Reviewing our Street Name Audit.html
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Part 12-Module 01-Lesson 03_Interview Fails/04. Interviewing Fails Lyla Fujiwara-CgK2HxdJzc8.es-MX.vtt
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Part 13-Module 01-Lesson 04_Design Principles/38. Data Ink Ratio-CJouyPxHb84.en.vtt
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Part 15-Module 01-Lesson 02_Design Principles/17. Data Ink Ratio-CJouyPxHb84.en.vtt
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components.html
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Part 11-Module 01-Lesson 10_Feature Scaling/11. MinMax Scaler in sklearn-lgoh5R05YM0.en.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/25. Dot Notation-OcPW6xp8DfE.en.vtt
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/10. Reviewing our Street Name Audit.html
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Part 12-Module 01-Lesson 05_Interview Practice/04. Query a SQL database.html
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Part 12-Module 01-Lesson 01_Ace Your Interview/01. Introduction.html
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Part 05-Module 01-Lesson 05_Data Quality/10. Wikipedia Infobox Dataset-hpyNAYJODqw.en.vtt
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Part 12-Module 01-Lesson 05_Interview Practice/07. Jimmy's Analysis of the Interview.html
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Part 13-Module 01-Lesson 04_Design Principles/38. Data Ink Ratio-CJouyPxHb84.pt-BR.vtt
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Part 15-Module 01-Lesson 02_Design Principles/17. Data Ink Ratio-CJouyPxHb84.pt-BR.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/13. Binomial Distribution-nXbucNJpP8I.zh-CN.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/03. Projects and Progress.html
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Part 03-Module 01-Lesson 15_PS 5b Additional Practice (Optional)/03. 9. IQ 150.html
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/02. Familiarize Yourself with the Dataset-JyX6j00Q2Cg.en-US.vtt
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/02. Familiarize Yourself with the Dataset-JyX6j00Q2Cg.en-US.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/16. Pandas Series apply()-c8SD8zn5FTo.pt-BR.vtt
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Part 12-Module 01-Lesson 03_Interview Fails/04. Interviewing Fails Lyla Fujiwara-CgK2HxdJzc8.pt-BR.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/17. Pandas Series apply()-c8SD8zn5FTo.pt-BR.vtt
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/02. Familiarize Yourself with the Dataset-JyX6j00Q2Cg.en.vtt
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/02. Familiarize Yourself with the Dataset-JyX6j00Q2Cg.en.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/11. Dangers of Statistics.html
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 2-W2tL3QSBi3k.ar.vtt
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/06. Matrix Multiplication Part 1.html
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Part 03-Module 01-Lesson 21_PS 8a Estimation/07. 8. Probability.html
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Part 03-Module 01-Lesson 20_L8 Estimation/index.html
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Part 03-Module 01-Lesson 25_PS 9b Additional Practice (Optional)/01. 10. Hypotheses.html
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/04. NumPy Arrays-7GeiZ8IVZfE.zh-CN.vtt
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/04. Data Model.html
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/05. NumPy Arrays-7GeiZ8IVZfE.zh-CN.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/01. Welcome to the DA Nanodegree Program.html
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/06. Iterating through Ways Tags.html
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Part 03-Module 01-Lesson 10_PS 3b Additional Practice (Optional)/11. 24. Median Given Histogram.html
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Part 03-Module 01-Lesson 21_PS 8a Estimation/04. 4. Increase Population SD.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/index.html
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Part 05-Module 01-Lesson 05_Data Quality/11. Auditing a Cross-Field Constraint-Y7TNXALXut8.en.vtt
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/02. Familiarize Yourself with the Dataset-JyX6j00Q2Cg.pt-BR.vtt
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/02. Familiarize Yourself with the Dataset-JyX6j00Q2Cg.pt-BR.vtt
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Part 03-Module 01-Lesson 21_PS 8a Estimation/03. 3. Increase Sample Size.html
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Part 09-Module 01-Lesson 01_What is EDA/04. Aude's Interest in Data.html
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Part 03-Module 01-Lesson 32_PS 11b Additional Practice (Optional)/08. 13. Decision.html
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Part 04-Module 01-Lesson 01_Anaconda/01. Introduction.html
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Part 16-Module 01-Lesson 01_Anaconda/01. Introduction.html
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/01. Intro.html
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely.html
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Part 03-Module 01-Lesson 21_PS 8a Estimation/06. 7. Standard Error.html
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection.html
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Part 21-Module 01-Lesson 05_Scripting/index.html
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network.html
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/20. Duration vs. Exposure-MsByTo7FRgs.en.vtt
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/03. Resume Structure.html
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Part 14-Module 01-Lesson 05_Analyzing Results/14. Multiple Metrics Example 2-nTeQi9MjgiA.en.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/01. Convey Your Skills Concisely.html
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Part 09-Module 01-Lesson 01_What is EDA/08. Aude Explores Coordinated Migration-7ihp6ofAJG8.ar.vtt
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Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/11. Question 10.html
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/02. Introduction.html
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/23. Learning Effects-nFpIDWPUDm8.zh-CN.vtt
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Part 04-Module 01-Lesson 02_Jupyter notebooks/05. Code cells.html
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/12. Congratulations.html
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Part 16-Module 01-Lesson 02_Jupyter notebooks/05. Code cells.html
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Part 03-Module 01-Lesson 08_L3 Central Tendency/index.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/26. DATE Functions Part II-UPWkDhW4cLI.ar.vtt
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Part 15-Module 01-Lesson 04_Telling Stories with Tableau/09. Learning Summary.html
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Part 05-Module 01-Lesson 05_Data Quality/14. Auditing Accuracy 2-5xY3sCBHkOk.en-US.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/14. Conclusion.html
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/36. Groups And Sets-Yb-91NVNgTA.ar.vtt
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Part 03-Module 01-Lesson 14_PS 5a Standardizing/03. 3. OkCupid.html
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Part 05-Module 01-Lesson 05_Data Quality/14. Auditing Accuracy 2-5xY3sCBHkOk.en.vtt
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Part 03-Module 01-Lesson 21_PS 8a Estimation/08. 9. Margin of Error.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/25. Empirical Variability Sanity Checking-6vxdVWIA6dI.zh-CN.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/14. Multiple Metrics Example 2-nTeQi9MjgiA.pt-BR.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/10. Welcome to the end of the lesson.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/07. History of AB Testing-NNiKGao0xnk.ar.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/08. Coding 2.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/22. How Page Views Affect Sensitivity-WFVj8QI_uto.ar.vtt
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Part 12-Module 02-Lesson 06_Graphs/03. Directions and Cycles.html
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Part 12-Module 02-Lesson 06_Graphs/06. Graph Representations.html
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Part 16-Module 03-Lesson 02_SQL Joins/14. Other JOINs-4edRxFmWUEw.ar.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare.html
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Part 09-Module 01-Lesson 01_What is EDA/09. Course Overview.html
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Part 21-Module 01-Lesson 04_Functions/02. Defining Functions-IP_tJYhynbc.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/19. Lessons Completed in First Week -nZq-Y2lfjpY.en.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/15. Standardizing Each Column Again-WmJKPUthUPw.en.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/15. Standardizing Each Column Again-WmJKPUthUPw.en.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/20. Duration vs. Exposure-MsByTo7FRgs.pt-BR.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/index.html
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Part 03-Module 01-Lesson 14_PS 5a Standardizing/10. 13. SD.html
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Part 11-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites.html
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Part 06-Module 01-Lesson 03_Analyzing Data/06. Aggregation Operators 1-mRNyMEoCoY0.ar.vtt
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection.html
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Part 12-Module 02-Lesson 06_Graphs/01. Graph Introduction.html
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Part 12-Module 02-Lesson 06_Graphs/07. Adjacency Matrices.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/index.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-ycbXO4xBEVw.ar.vtt
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Part 12-Module 01-Lesson 05_Interview Practice/02. Describe your latest data project-cXluuqCVg18.en.vtt
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Part 04-Module 03-Lesson 01_Investigate a Dataset/04. Project Workspace Complete and Submit Project.html
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Part 14-Module 01-Lesson 05_Analyzing Results/07. Sanity Checking Wrapup-rCAYdZk5O2E.en.vtt
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/01. Introduction.html
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Part 14-Module 01-Lesson 06_Final Project/10. Congratulations!.html
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/03. Resume Structure.html
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/16. Pandas groupby()-smBMJlpWdVI.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/16. Pandas groupby()-smBMJlpWdVI.zh-CN.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/05. Resume Reflection.html
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Part 03-Module 01-Lesson 21_PS 8a Estimation/09. 10. 95 CI.html
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Part 03-Module 01-Lesson 24_PS 9a Hypothesis Testing/09. 9. Type I Error.html
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Part 03-Module 01-Lesson 21_PS 8a Estimation/05. 6. Critical Values 95 CI.html
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Part 05-Module 02-Lesson 02_Problem Set Data and Tables/02. WARM UP - Translate Query #1.html
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Part 05-Module 02-Lesson 02_Problem Set Data and Tables/03. WARM UP - Translate Query #2.html
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Part 12-Module 02-Lesson 04_Maps and Hashing/09. String Keys.html
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Part 12-Module 02-Lesson 06_Graphs/02. What Is a Graph.html
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/03. Resume Structure.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-QoEqPotgMbA.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-v4UGBUB6jO4.pt-BR.vtt
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Part 12-Module 02-Lesson 06_Graphs/09. Graph Traversal.html
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/01. Choose Your own Algorithm.html
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/03. Choose Your Own Adventure.html
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Part 12-Module 02-Lesson 06_Graphs/13. Eulerian Path.html
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Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5DvUOwA7xhU.ar.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/15. Extracting Entities-aJD8WJa3-9A.ar.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/16. Pandas Series apply()-c8SD8zn5FTo.en-US.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/17. Pandas Series apply()-c8SD8zn5FTo.en-US.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/16. Pandas Series apply()-c8SD8zn5FTo.en.vtt
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Part 12-Module 02-Lesson 06_Graphs/04. Connectivity.html
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/17. Pandas Series apply()-c8SD8zn5FTo.en.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size-MLzRdgcFYQQ.ar.vtt
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Part 05-Module 01-Lesson 06_Problem Set Data Quality/02. Making a Choice.html
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/01. Intro.html
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/04. Meet Chris.html
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Part 21-Module 01-Lesson 03_Control Flow/25. Break and Continue-F6qJAv9ts9Y.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/07. What is a Projection-QjVNXfI8YRk.ar.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/07. Sanity Checking Wrapup-rCAYdZk5O2E.pt-BR.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/05. Investigation Process.html
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Part 10-Module 01-Lesson 03_Udacity Professional Profile/08. Experience.html
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Part 03-Module 01-Lesson 15_PS 5b Additional Practice (Optional)/08. 22. BBC - Temporal.html
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Part 03-Module 01-Lesson 15_PS 5b Additional Practice (Optional)/09. 23. BBC - What Score.html
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Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-FORb9Tja-p0.ar.vtt
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Part 03-Module 01-Lesson 15_PS 5b Additional Practice (Optional)/06. 20. BBC - Sleep.html
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Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/13. Scott's Advice to Break into Data Vis-v5ywQMRCxMg.ar.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/04. Algorithm Options.html
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Part 09-Module 01-Lesson 05_Explore Two Variables/25. Smoothing Conditional Means-hxk2cgdChUw.pt-BR.vtt
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/04. Element-wise Matrix Operations.html
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Part 03-Module 01-Lesson 15_PS 5b Additional Practice (Optional)/07. 21. BBC - Recognition.html
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Part 04-Module 01-Lesson 02_Jupyter notebooks/07. Keyboard shortcuts.html
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Part 16-Module 01-Lesson 02_Jupyter notebooks/07. Keyboard shortcuts.html
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Part 14-Module 01-Lesson 05_Analyzing Results/16. Analyzing Multiple Metrics-mbHnQ_EdrZ8.zh-CN.vtt
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Part 21-Module 01-Lesson 01_Why Python Programming/02. Welcome to the Course!.html
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/09. L4_Mini Project.html
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/index.html
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Part 12-Module 01-Lesson 02_Practice Behavioral Questions/01. Introduction.html
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Part 02-Module 01-Lesson 01_Intro to Research Methods/index.html
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Part 04-Module 01-Lesson 02_Jupyter notebooks/02. Installing Jupyter Notebook.html
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Part 03-Module 01-Lesson 24_PS 9a Hypothesis Testing/04. 4. Standard Error.html
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Part 03-Module 01-Lesson 22_PS 8b Additional Practice (Optional)/05. 15. Margin of Error.html
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Part 03-Module 01-Lesson 22_PS 8b Additional Practice (Optional)/03. 13. Standard Error.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/08. Overview of Business Example-tlSe7H9BDy8.ar.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/index.html
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Part 12-Module 01-Lesson 03_Interview Fails/03. Interviewing Fails Siya Raj Purohit.html
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Part 11-Module 01-Lesson 02_Naive Bayes/18. Gaussian NB Example-wpnDwiqTCJA.pt-BR.vtt
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/index.html
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Part 12-Module 01-Lesson 03_Interview Fails/04. Interviewing Fails Lyla Fujiwara.html
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Part 03-Module 01-Lesson 07_Google Spreadsheet Tutorial/01. Tutorial.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/03. XML Design Principles-eQpSC0IFhv0.zh-CN.vtt
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Part 11-Module 01-Lesson 01_Welcome to Machine Learning/03. Introduction, Part III.html
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Part 11-Module 01-Lesson 16_Tying It All Together/02. Summary.html
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/index.html
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/index.html
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Part 07-Module 01-Lesson 01_GitHub Review/index.html
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Part 11-Module 01-Lesson 14_Validation/index.html
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/index.html
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Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-4GBJk6R0pb4.en.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/index.html
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Part 13-Module 01-Lesson 04_Design Principles/38. Data Ink Ratio-CJouyPxHb84.zh-CN.vtt
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Part 11-Module 01-Lesson 16_Tying It All Together/04. Outro.html
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Part 12-Module 01-Lesson 03_Interview Fails/01. Interview Fails.html
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Part 05-Module 02-Lesson 05_Deeper into SQL/03. Normalized Design Part Two-l6SDnhM7B_k.ar.vtt
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Part 21-Module 01-Lesson 01_Why Python Programming/01. Instructor.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/29. 11 CASE V2-BInXuTY_FzE.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-MlE3BuOvWnU.ar.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment -BNRJdhA8_s8.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/34. Completing the Update Function-lUYD6lldDeU.en.vtt
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.ar.vtt
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/02. Elevator Pitch-S-nAHPrkQrQ.ar.vtt
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/08. Auditing Street Names-c0IcUiF_kXs.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/32. SD Social Networkers-cy8BwWl36Q4.pt-BR.vtt
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Part 11-Module 01-Lesson 08_Outliers/index.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/15. Nested Selections-y3kJorrQrJg.en.vtt
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Part 03-Module 01-Lesson 25_PS 9b Additional Practice (Optional)/02. 11. Standard Error.html
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Part 03-Module 01-Lesson 12_PS 4 Variability/index.html
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Part 12-Module 01-Lesson 04_Land a Job Offer/01. Land a Job Offer.html
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Part 04-Module 02-Lesson 01_Data Analysis Process/22. Comparing the Two Student Groups-6UYEM0XUSGQ.pt-BR.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/14. Multiple Metrics Example 2-nTeQi9MjgiA.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/06. Flat File Structure-bLKVRIhrZUY.pt-BR.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size-4-MF0UZac8o.ar.vtt
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Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-FDSmlIBy7ko.ar.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/29. From Bars to Circles to Lines-MA-n0Hi3Wyg.ar.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/18. Gotchas Changes Over Time-P7Hso-EoWvA.pt-BR.vtt
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Part 05-Module 01-Lesson 05_Data Quality/10. Wikipedia Infobox Dataset-hpyNAYJODqw.zh-CN.vtt
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/img/lag-1-innerquery.png
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Part 06-Module 01-Lesson 01_Working with MongoDB/19. Exists-j5l5UvE3Odw.ar.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/13. Getting Data into MongoDB-hi6g1NE3sPk.ar.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/09. HTML Structure-UjCbXQ8Coic.ar.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/08. Números inteiros e floats-MiJ1vfWp-Ts.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/13. Uniqueness and Keys-TIayTr4y9RA.ar.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/18. JOINs and Filtering-aI1kbDDNs4w.ar.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 Solution-E5tAoCK6GcQ.pt-BR.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/13. Quick Sort-kUon6854joI.en-US.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/05. Brainstorming-LJFYhMDCCsU.en-US.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/23. The Facebook Offering-ORLP-phGXMU.zh-CN.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/13. Quick Sort-kUon6854joI.en.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/05. Brainstorming-LJFYhMDCCsU.en.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/04. The Aggregation Pipeline-0sl_mbV-fho.pt-BR.vtt
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Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-YbVuN2KOlt4.ar.vtt
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Part 11-Module 01-Lesson 16_Tying It All Together/03. End of Content.html
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Part 05-Module 01-Lesson 05_Data Quality/index.html
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Part 21-Module 01-Lesson 04_Functions/index.html
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Part 14-Module 01-Lesson 05_Analyzing Results/07. Sanity Checking Wrapup-rCAYdZk5O2E.zh-CN.vtt
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Part 15-Module 01-Lesson 02_Design Principles/index.html
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Part 05-Module 01-Lesson 05_Data Quality/11. Auditing a Cross-Field Constraint-Y7TNXALXut8.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/16. JSON File Structure-hO2CayzZBoA.pt-BR.vtt
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Part 11-Module 01-Lesson 16_Tying It All Together/01. Introduction.html
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Part 16-Module 03-Lesson 03_SQL Aggregations/25. DATE Functions I-E7Z6GMFVmIY.ar.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/index.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/04. Load D3 in the JavaScript Console-mGyo6dOf0So.en-US.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/31. Layout and Scales-BQWN9ImjUFE.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-5571wc0iWCI.ja.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/04. Load D3 in the JavaScript Console-mGyo6dOf0So.en.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/04. Assessing the Quality of Data Pt. 2-8onBHqvvrig.ar.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-qgwygpD0eN8.ar.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/11. D3 Chain Syntax and Changing the Navbar-DQ9_HknCsAI.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/03. Two-Dimensional NumPy Arrays-UFcCmB7Xvvs.ar.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/index.html
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/03. Two-Dimensional NumPy Arrays-UFcCmB7Xvvs.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-9JfaMZcSlQA.ar.vtt
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Part 11-Module 01-Lesson 11_Text Learning/06. Bag of Words in Sklearn-aCdg-d_476Y.zh-CN.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/10. Merge Sort-K916wfSzKxE.zh-CN.vtt
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Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/index.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/02. Data Modeling in MongoDB-6sDkIE_nAGI.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-v4UGBUB6jO4.zh-CN.vtt
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Part 04-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.ar.vtt
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Part 16-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-5571wc0iWCI.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-O9d9dKyHtIc.en-US.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-O9d9dKyHtIc.en.vtt
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Part 19-Module 01-Lesson 02_Design/03. Exploratory vs. Explanatory Analysis-wvgBSMks4p8.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/25. Demystifying D3-y7QK8XMHyDQ.en.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/03. Finding the Best Movies-aq3qM2EkwrI.zh-CN.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/12. Related Tables-lMwSjDYgCq0.ar.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/28. Multi Update-tuXc0Ycy_yM.ar.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/17. Multicollinearity VIFs-wbtrXMusDe8.zh-CN.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/08. Intro to PyMongo-h6M4x9aXx5g.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/index.html
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Part 06-Module 01-Lesson 03_Analyzing Data/04. The Aggregation Pipeline-0sl_mbV-fho.en.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/index.html
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Part 17-Module 01-Lesson 08_Python Probability Practice/02. Simulating Coin Flips-7YtQNZ3iy6o.ar.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/06. Accessing Elements of a DataFrame-4RmQYWI8lY4.ar.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/06. Accessing Elements of a DataFrame-4RmQYWI8lY4.ar.vtt
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Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Part II-1GRv1S6K8gQ.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/index.html
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Part 21-Module 01-Lesson 05_Scripting/06. Programming Environment Setup-EKxDnCK0NAk.pt-BR.vtt
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/04. Meet Chris-0ccflD9x5WU.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/07. Small Multiples-HS_dsOQfwz8.ar.vtt
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Part 19-Module 01-Lesson 02_Design/08. Data Ink Ratio-gW2FapuYV4A.zh-CN.vtt
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Part 12-Module 01-Lesson 02_Practice Behavioral Questions/06. A Problem and How You Dealt With It-7IKqdW30GvQ.en.vtt
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Part 19-Module 01-Lesson 02_Design/13. Using Color-6bAedqD3ilw.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/20. How Scales Work-4zqm8dz7Z-k.en-US.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/20. How Scales Work-4zqm8dz7Z-k.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/25. Correlation Does Not Imply Causation-aeEhfjPFiCw.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/index.html
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Part 14-Module 01-Lesson 04_Designing an Experiment/12. Target Population Example-XsyavvSGjLM.ar.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/17. More Work Than We Thought-vgJ0ZlxzSiw.ar.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/02. Twitter Data Set-xiqleK_px_Q.ar.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2-ZXy8jgywY5g.en.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/18. Sensitivity and Robustness-T2QI3p0yDNk.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet -K-Owid_mf8o.en.vtt
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Part 11-Module 01-Lesson 09_Clustering/10. K-Means Clustering Visualization 2-fQXXa-CAoS0.ar.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/22. Comparing the Two Student Groups-6UYEM0XUSGQ.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/14. Writing Code with DB API-Zd0PAgb6vY4.ar.vtt
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Part 17-Module 01-Lesson 13_Case Study AB tests/index.html
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/27. Empirical Variability Bootstrapping-YW-uud_btQ8.ar.vtt
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Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules-jPGyFgcIvsM.pt-BR.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/index.html
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Part 05-Module 02-Lesson 05_Deeper into SQL/index.html
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Part 11-Module 01-Lesson 13_PCA/29. When to Use PCA-hJZHcmJBk1o.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/06. Flat File Structure-bLKVRIhrZUY.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.th.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.th.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/08. Números inteiros e floats-MiJ1vfWp-Ts.en.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/36. Groups And Sets-Yb-91NVNgTA.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/18. Combining Pandas DataFrames-_Rx9Z-uURQk.zh-CN.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/08. Standard Deviation Calculation-H5zA1A-XPoY.ar.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/18. Combining Pandas DataFrames-_Rx9Z-uURQk.zh-CN.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 Solution-E5tAoCK6GcQ.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/01. ML in The Google Self-Driving Car-lL16AQItG1g.zh-CN.vtt
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/index.html
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/05. Iterating through Ways Tags-GYhOEJ8EXkg.en.vtt
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/06. Iterating through Ways Tags-GYhOEJ8EXkg.en.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-oEhevl5DWpk.ar.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-xsdj1qJwgk4.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/35. Returns in the Data Binding Process-OwyrjSRb2xo.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/32. SD Social Networkers-cy8BwWl36Q4.en-US.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/32. SD Social Networkers-cy8BwWl36Q4.en.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet -K-Owid_mf8o.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/25. Smoothing Conditional Means-hxk2cgdChUw.zh-CN.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/13. Strings-ySZDrs-nNqg.zh-CN.vtt
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/05. Iterating through Ways Tags-GYhOEJ8EXkg.pt-BR.vtt
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/06. Iterating through Ways Tags-GYhOEJ8EXkg.pt-BR.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/16. JSON File Structure-hO2CayzZBoA.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/01. Independent Samples-K25Xtqr2WvI.en.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/32. Binding Data-yW9LEMFOzgY.ar.vtt
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Part 03-Module 01-Lesson 29_PS 10b t-Tests, Part 2/index.html
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/10. Reviewing our Street Name Audit-pH3VusOq9tc.zh-CN.vtt
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/index.html
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Part 21-Module 01-Lesson 04_Functions/02. Defining Functions-IP_tJYhynbc.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/11. Flashforward 1-Sr5v0i9m_sw.en.vtt
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Part 12-Module 02-Lesson 05_Trees/index.html
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Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/13. Scott's Advice to Break into Data Vis-v5ywQMRCxMg.en.vtt
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/index.html
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Part 09-Module 01-Lesson 01_What is EDA/03. Why learn EDA-YM68DrqJw1I.ja.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/27. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.ar.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.ar.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/30. EDA vs Sketching Data Visualizations-hFlVFyatBF0.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/index.html
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Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet -K-Owid_mf8o.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/25. Correlation Does Not Imply Causation-aeEhfjPFiCw.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.th.vtt
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Part 09-Module 01-Lesson 04_Problem Set Explore One Variable/index.html
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Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/index.html
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Part 11-Module 01-Lesson 02_Naive Bayes/18. Gaussian NB Example-wpnDwiqTCJA.zh-CN.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/14. Efficiency of Quick Sort-aMb5GHPGQ1U.en-US.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/16. Debugging and Inspecting Chart Objects-XYMtkn0DyIM.ar.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/14. Efficiency of Quick Sort-aMb5GHPGQ1U.en.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/07. Visual Assessment -GVVibuIg3Ro.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/31. R Squared in SKlearn-Dxf1I4IE6co.en.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/08. Calculating Correlation-isBv5D88Nso.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/08. Calculating Correlation-isBv5D88Nso.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/11. Flashforward 1-Sr5v0i9m_sw.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-O9d9dKyHtIc.ja.vtt
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Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-FORb9Tja-p0.ja.vtt
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Part 11-Module 01-Lesson 13_PCA/28. PCA in sklearn-SBYdqlLgbGk.zh-CN.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/index.html
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 2-W2tL3QSBi3k.pt-BR.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/27. Set Unset-bgOky14w77Q.zh-CN.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/13. Metric Definition Example-1EoJTK_S0mk.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-ycbXO4xBEVw.pt-BR.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys-fnbLMcd0FGQ.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/07. What is a Projection-QjVNXfI8YRk.en.vtt
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Part 11-Module 01-Lesson 01_Welcome to Machine Learning/01. Introduction-ICKBWIkfeJ8.zh-CN.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/20. Notation for Random Variables-8NxTW1u4s-Y.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/07. How to Lie with Bar Charts-75c7a4R4pZ0.pt-BR.vtt
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Part 12-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier-Uy89Ff49pRc.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/18. Visual Encodings-14FJU1kP6-M.zh-CN.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/07. Visual Encodings - Data Visualization and D3.js-14FJU1kP6-M.zh-CN.vtt
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Part 19-Module 01-Lesson 02_Design/13. Using Color-6bAedqD3ilw.en.vtt
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Part 08-Module 01-Lesson 01_Conduct a Job Search/03. Target Your Application to An Employer-X9JBzbrkcvs.zh-CN.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-V7zAB9dUaFY.ar.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/13. Pandas Series-V7zAB9dUaFY.ar.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-QoEqPotgMbA.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/07. Fixing Data Types-7NSYtdVrlRE.zh-CN.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/02. Arithmetic Operators-M8TIOK2P2yw.ar.vtt
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assets/css/fonts/KaTeX_Size3-Regular.woff
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Part 11-Module 01-Lesson 12_Feature Selection/15. Regularization-l9V5tlIWTvs.ar.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/08. Document Selectors And Queries-xQbKGc-Ptao.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-0L3Obq4FSVQ.pt-BR.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/index.html
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Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-TjY0Q66Yh-s.ar.vtt
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Part 09-Module 01-Lesson 02_R Basics/index.html
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/04. 29 Number Summary-gzUN5zKLHjQ.ar.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/02. Standard Error-GTsnxTCjmcM.en.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/12. Intro to JSON-Fi7RjhBLobY.zh-CN.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/index.html
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Part 13-Module 01-Lesson 02_D3 Building Blocks/15. Nested Selections-y3kJorrQrJg.zh-CN.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. Performance Tuning 1-5mVfYZ_bfRo.ar.vtt
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Part 12-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier-Uy89Ff49pRc.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/24. Annotations World Cup Attendance Chart-Aq39o9xrW5A.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/08. Defining Metrics Other Techniques-gEO8il9GU3M.zh-CN.vtt
4.8 kB
Part 19-Module 01-Lesson 02_Design/15. Shape, Size, and other Tools-fzEliHW3ZLM.ar.vtt
4.8 kB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/10. Welcome to the end of the lesson-nWFJ_eOU27I.ar.vtt
4.7 kB
Part 13-Module 01-Lesson 07_Narrative Structures/07. How to Lie with Bar Charts-75c7a4R4pZ0.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/31. R Squared in SKlearn-Dxf1I4IE6co.pt-BR.vtt
4.7 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/07. What is a Projection-QjVNXfI8YRk.pt-BR.vtt
4.7 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/25. L2 06 Lists Methods V1-tz2Ja1Eaeqo.en.vtt
4.7 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/03. Data Analysis Process-cAceF0h4vpI.en.vtt
4.7 kB
Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/13. Scott's Advice to Break into Data Vis-v5ywQMRCxMg.pt-BR.vtt
4.7 kB
Part 05-Module 02-Lesson 03_Elements of SQL/index.html
4.7 kB
Part 05-Module 02-Lesson 01_Data and Tables/index.html
4.7 kB
Part 09-Module 01-Lesson 01_What is EDA/08. Aude Explores Coordinated Migration-7ihp6ofAJG8.en.vtt
4.7 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/03. Good Data Visualization-ePekYbKs60U.ar.vtt
4.7 kB
Part 11-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-GdsLRKjjKLw.zh-CN.vtt
4.7 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/13. Series Indexes-RK6CPtXdK5Q.zh-CN.vtt
4.7 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/14. Series Indexes-RK6CPtXdK5Q.zh-CN.vtt
4.7 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size-MLzRdgcFYQQ.pt-BR.vtt
4.7 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/18. Joining Subqueries-rxy-fE5GeLY.ar.vtt
4.7 kB
Part 11-Module 01-Lesson 13_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.ar.vtt
4.7 kB
Part 13-Module 01-Lesson 07_Narrative Structures/62. Adding Circles to the Legend-FlbCPYGCKqk.ar.vtt
4.7 kB
Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.th.vtt
4.7 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/02. Intro to XML-eIVifBVJQIw.ar.vtt
4.7 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.ar.vtt
4.7 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.ar.vtt
4.7 kB
Part 13-Module 01-Lesson 07_Narrative Structures/25. Demystifying D3-y7QK8XMHyDQ.zh-CN.vtt
4.7 kB
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-vLlj5nNj8x4.ar.vtt
4.7 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/15. Filtering and Segmenting Example-WgM3cBEtkqg.pt-BR.vtt
4.7 kB
Part 07-Module 01-Lesson 01_GitHub Review/04. Interview with Art - Part 1-ClLYamtaO-Q.ar.vtt
4.7 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/44. Adding Events to Buttons-aejs122BTzA.zh-CN.vtt
4.7 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-E3NhvAC3Ghw.ar.vtt
4.7 kB
Part 18-Module 02-Lesson 01_Gathering Data/06. Flat File Structure-bLKVRIhrZUY.zh-CN.vtt
4.7 kB
Part 14-Module 01-Lesson 05_Analyzing Results/11. Gotchas Simpson’s Paradox-Tx_jtCfrbt0.ar.vtt
4.7 kB
Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-0L3Obq4FSVQ.en.vtt
4.7 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2-ZXy8jgywY5g.zh-CN.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/19. String Methods-Bv7CAxVOONs.ar.vtt
4.7 kB
Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-YaZu4waSryo.ar.vtt
4.7 kB
Part 13-Module 01-Lesson 07_Narrative Structures/02. Approaches to Journalism-AxFSDfKP7Zs.pt-BR.vtt
4.7 kB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/08. Auditing Street Names-c0IcUiF_kXs.zh-CN.vtt
4.7 kB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/09. Auditing Street Names-c0IcUiF_kXs.zh-CN.vtt
4.7 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/29. Removing Documents-oFWNOvxuIRQ.ar.vtt
4.7 kB
Part 07-Module 01-Lesson 01_GitHub Review/13. Interview with Art - Part 3-M6PKr3S1rPg.pt-BR.vtt
4.7 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/46. World Cup Code and Narrative Recap-lnHEvGeech0.zh-CN.vtt
4.7 kB
Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/index.html
4.7 kB
Part 12-Module 01-Lesson 05_Interview Practice/04. Query a SQL database-UVSFLWdAKl4.pt-BR.vtt
4.7 kB
Part 17-Module 01-Lesson 06_Conditional Probability/index.html
4.7 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -CSW2i2jIqyA.ar.vtt
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Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Part II-1GRv1S6K8gQ.zh-CN.vtt
4.7 kB
Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5DvUOwA7xhU.en.vtt
4.7 kB
Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/index.html
4.7 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/06. Accessing Elements of a DataFrame-hZp9cVuiPo0.ar.vtt
4.6 kB
Part 09-Module 01-Lesson 01_What is EDA/08. Aude Explores Coordinated Migration-7ihp6ofAJG8.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/06. Accessing Elements of a DataFrame-hZp9cVuiPo0.ar.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/02. Problems Solved by Data Analysts-jZEbCVZzwUk.ar.vtt
4.6 kB
Part 12-Module 02-Lesson 03_Searching and Sorting/index.html
4.6 kB
Part 15-Module 01-Lesson 02_Design Principles/img/strip-plot.png
4.6 kB
Part 03-Module 01-Lesson 27_PS 10a t-Tests, Part 1/index.html
4.6 kB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/index.html
4.6 kB
Part 12-Module 02-Lesson 03_Searching and Sorting/13. Quick Sort-kUon6854joI.pt-BR.vtt
4.6 kB
Part 05-Module 02-Lesson 06_Problem Set Deeper Into SQL/index.html
4.6 kB
Part 09-Module 01-Lesson 01_What is EDA/08. Aude Explores Coordinated Migration-7ihp6ofAJG8.ja.vtt
4.6 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-GXT_vXBA0vQ.ar.vtt
4.6 kB
Part 12-Module 02-Lesson 03_Searching and Sorting/13. Quick Sort-kUon6854joI.zh-CN.vtt
4.6 kB
Part 13-Module 01-Lesson 04_Design Principles/06. Common Chart Types-xD2_AU6atqA.zh-CN.vtt
4.6 kB
Part 15-Module 01-Lesson 02_Design Principles/02. Tipos Comuns de Gráficos-xD2_AU6atqA.zh-CN.vtt
4.6 kB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/06. Appending And NumPy-fdpKvovBMe4.ar.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/22. Interactions Higher Order Terms-gMHwogzqPOk.pt-BR.vtt
4.6 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/15. Calculating a Confidence Interval-HGYW-skXvY4.zh-CN.vtt
4.6 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-QoEqPotgMbA.en.vtt
4.6 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/09. Investigating the Data-zJ_wWRTQUTs.ar.vtt
4.6 kB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/04. Meet Chris-0ccflD9x5WU.es-MX.vtt
4.6 kB
Part 03-Module 01-Lesson 17_PS 6 Normal Distribution/index.html
4.6 kB
Part 03-Module 01-Lesson 10_PS 3b Additional Practice (Optional)/index.html
4.6 kB
Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-x-8-2zy8gmI.ar.vtt
4.6 kB
Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-TIgfjmp-4BA.pt-BR.vtt
4.6 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-gfuknvEP2ro.ar.vtt
4.6 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/02. Metric Definition Overview-pOxyL1lwBIw.zh-CN.vtt
4.6 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/26. Empirical Confidence Intervals-ca8GQmr7B8g.zh-CN.vtt
4.6 kB
Part 17-Module 01-Lesson 05_Binomial Distribution/index.html
4.6 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-uoHzcmf4yXU.pt-BR.vtt
4.6 kB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/index.html
4.6 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1-mUfrDUEEa_k.ar.vtt
4.6 kB
Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/index.html
4.6 kB
Part 12-Module 01-Lesson 05_Interview Practice/index.html
4.6 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/22. How Page Views Affect Sensitivity-WFVj8QI_uto.pt-BR.vtt
4.6 kB
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-spVqFnSvlIU.pt-BR.vtt
4.6 kB
Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-TIgfjmp-4BA.en.vtt
4.6 kB
Part 15-Module 01-Lesson 02_Design Principles/img/jet.png
4.6 kB
Part 21-Module 01-Lesson 05_Scripting/21. The Standard Library-Fw3vf0tDrJM.ar.vtt
4.6 kB
Part 19-Module 01-Lesson 02_Design/05. What Makes a Bad Visual-zbvB_9f7bFs.ar.vtt
4.6 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/04. Consistency of Diversion-im8-LLU5J_Y.zh-CN.vtt
4.6 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-O9d9dKyHtIc.zh-CN.vtt
4.6 kB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.ar.vtt
4.6 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-Zdl01HMSjTw.en.vtt
4.6 kB
Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-fRNDqy-le8U.ar.vtt
4.6 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/20. Clean Define-qHB4jsqcfi4.ar.vtt
4.6 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 2-W2tL3QSBi3k.en.vtt
4.6 kB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/04. Meet Chris-0ccflD9x5WU.pt-BR.vtt
4.6 kB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/22. Interactions Higher Order Terms-gMHwogzqPOk.en.vtt
4.6 kB
Part 09-Module 01-Lesson 01_What is EDA/03. Why learn EDA-YM68DrqJw1I.pt-BR.vtt
4.6 kB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/06. A Problem and How You Dealt With It-7IKqdW30GvQ.zh-CN.vtt
4.6 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/20. Absolute or Relative Difference-TNcT_v2g3OQ.ar.vtt
4.6 kB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/index.html
4.6 kB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.ar.vtt
4.6 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/03. Data Analysis Process-cAceF0h4vpI.pt-BR.vtt
4.6 kB
Part 05-Module 01-Lesson 05_Data Quality/15. Auditing Completeness-PMbcv9AYQT4.pt-BR.vtt
4.6 kB
Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-5571wc0iWCI.zh-CN.vtt
4.6 kB
Part 16-Module 03-Lesson 01_Basic SQL/11. SELECT FROM Statements-urOYuuav4BY.ar.vtt
4.6 kB
Part 18-Module 02-Lesson 01_Gathering Data/22. SELECT FROM Statements-urOYuuav4BY.ar.vtt
4.6 kB
Part 13-Module 01-Lesson 07_Narrative Structures/46. Inspecting Data with Functions--itFNdnc5ns.pt-BR.vtt
4.6 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/05. Lets Make a Map-mOZuq2JoN-k.zh-CN.vtt
4.6 kB
Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/index.html
4.6 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/25. L2 06 Lists Methods V1-tz2Ja1Eaeqo.pt-BR.vtt
4.6 kB
Part 14-Module 01-Lesson 05_Analyzing Results/17. Drawing Conclusions-CZQ-nZyUG7g.en.vtt
4.5 kB
Part 05-Module 01-Lesson 05_Data Quality/17. Consistency-_5AnMdslWg4.ar.vtt
4.5 kB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/index.html
4.5 kB
Part 21-Module 01-Lesson 03_Control Flow/25. Break and Continue-F6qJAv9ts9Y.pt-BR.vtt
4.5 kB
Part 14-Module 01-Lesson 05_Analyzing Results/15. Multiple Metrics Example 3-XByoblkCgfE.zh-CN.vtt
4.5 kB
Part 14-Module 01-Lesson 05_Analyzing Results/18. Gotchas Changes Over Time-P7Hso-EoWvA.zh-CN.vtt
4.5 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-w6CLWh1dLCU.ja.vtt
4.5 kB
Part 13-Module 01-Lesson 07_Narrative Structures/41. Parsing Data Before the Draw Function-WALbqgiDHNI.ar.vtt
4.5 kB
Part 21-Module 01-Lesson 05_Scripting/26. Third Party Libraries And Package Managers-epOze9gC6T4.ar.vtt
4.5 kB
Part 13-Module 01-Lesson 05_Dimple.js/01. Dimple Interlude-bo8_lJucTPI.ar.vtt
4.5 kB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/10. Worst Case and Approximation-ZYcmui02J40.en-US.vtt
4.5 kB
Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/index.html
4.5 kB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/10. Worst Case and Approximation-ZYcmui02J40.en.vtt
4.5 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/20. Practical, or Substantive, Significance-Q576t5aaZ34.pt-BR.vtt
4.5 kB
Part 14-Module 01-Lesson 05_Analyzing Results/03. Choosing Invariants-E1ePfjcVH3I.pt-BR.vtt
4.5 kB
Part 17-Module 01-Lesson 03_Admissions Case Study/index.html
4.5 kB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/index.html
4.5 kB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/index.html
4.5 kB
Part 18-Module 02-Lesson 01_Gathering Data/11. Flashforward 1-Sr5v0i9m_sw.zh-CN.vtt
4.5 kB
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.ar.vtt
4.5 kB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/04. Meet Chris-0ccflD9x5WU.zh-CN.vtt
4.5 kB
Part 11-Module 01-Lesson 13_PCA/23. PCA for Feature Transformation-8kUPRUEMCA8.pt-BR.vtt
4.5 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/09. Metric Choice-BeIy4A6YKrY.pt-BR.vtt
4.5 kB
Part 06-Module 01-Lesson 03_Analyzing Data/06. Aggregation Operators 1-mRNyMEoCoY0.pt-BR.vtt
4.5 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/14. Adding a DataFrame to a Series-K2sUmPodhqg.pt-BR.vtt
4.5 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/14. Adding a DataFrame to a Series-K2sUmPodhqg.pt-BR.vtt
4.5 kB
Part 11-Module 01-Lesson 14_Validation/10. Practical Advice for K-Fold in sklearn-COVRSk0GDEE.zh-CN.vtt
4.5 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/31. Layout and Scales-BQWN9ImjUFE.zh-CN.vtt
4.5 kB
Part 03-Module 01-Lesson 14_PS 5a Standardizing/index.html
4.5 kB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/index.html
4.5 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values-l3ergsxocok.ar.vtt
4.5 kB
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-spVqFnSvlIU.en.vtt
4.5 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/29. Collecting Participating Countries-ha6kGtT9XMQ.ar.vtt
4.5 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values-l3ergsxocok.ar.vtt
4.5 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-fo4MJMkwhYU.ar.vtt
4.5 kB
Part 11-Module 01-Lesson 09_Clustering/01. Unsupervised Learning-Mx9f99bRB3Q.ar.vtt
4.5 kB
Part 11-Module 01-Lesson 14_Validation/03. TrainTest Split in sklearn-lSwvUmZCvco.pt-BR.vtt
4.5 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-6CiZB0N7y64.ar.vtt
4.5 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-6CiZB0N7y64.ar.vtt
4.5 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/15. Filtering and Segmenting Example-WgM3cBEtkqg.en.vtt
4.5 kB
Part 13-Module 01-Lesson 04_Design Principles/51. D3 Functions-4OkB_Ybo0i0.ar.vtt
4.5 kB
Part 13-Module 01-Lesson 07_Narrative Structures/46. Inspecting Data with Functions--itFNdnc5ns.en.vtt
4.5 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/22. How Page Views Affect Sensitivity-WFVj8QI_uto.en.vtt
4.5 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/14. Helpful Symbols-w4_8YCp-9fI.ar.vtt
4.5 kB
Part 13-Module 01-Lesson 05_Dimple.js/30. EDA vs Sketching Data Visualizations-hFlVFyatBF0.en.vtt
4.5 kB
Part 13-Module 01-Lesson 07_Narrative Structures/43. D3 Parsing Dates and Times-DrOoJJWRAno.ar.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/14. Procedure-6rSJRr9OtHM.ar.vtt
4.5 kB
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-7CVlKQ3UjUI.ar.vtt
4.5 kB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/05. How Does MLR Work-bvM6eUYyurA.zh-CN.vtt
4.5 kB
Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-0L3Obq4FSVQ.ja.vtt
4.5 kB
Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-FORb9Tja-p0.pt-BR.vtt
4.5 kB
Part 18-Module 02-Lesson 01_Gathering Data/13. Text File Structure-O4qEWpXZLQg.ar.vtt
4.5 kB
Part 16-Module 03-Lesson 03_SQL Aggregations/29. 11 CASE V2-BInXuTY_FzE.zh-CN.vtt
4.5 kB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/index.html
4.5 kB
Part 18-Module 02-Lesson 01_Gathering Data/16. JSON File Structure-hO2CayzZBoA.zh-CN.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/12. Gathering Data-JsVg95-amjI.ar.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/15. Extracting Entities-aJD8WJa3-9A.en-US.vtt
4.5 kB
Part 11-Module 01-Lesson 10_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.ar.vtt
4.5 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/15. Extracting Entities-aJD8WJa3-9A.en.vtt
4.5 kB
Part 05-Module 02-Lesson 02_Problem Set Data and Tables/index.html
4.5 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/16. Type Type Conversion-yN6Fam_vZrU.ar.vtt
4.5 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-9L9bhMCHQ-M.ar.vtt
4.5 kB
Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-joTa_FeMZ2s.ar.vtt
4.5 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-Q2M8xyY47fc.ar.vtt
4.5 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/10. Techniques to Gather Additional Data-6mTsvU0ML94.pt-BR.vtt
4.5 kB
Part 13-Module 01-Lesson 07_Narrative Structures/02. Approaches to Journalism-AxFSDfKP7Zs.en.vtt
4.5 kB
Part 03-Module 01-Lesson 09_PS 3a Central Tendency/index.html
4.5 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/04. Load D3 in the JavaScript Console-mGyo6dOf0So.zh-CN.vtt
4.5 kB
Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-4GBJk6R0pb4.zh-CN.vtt
4.5 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/36. Groups And Sets-Yb-91NVNgTA.en.vtt
4.4 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/22. Looking at Samples of Households-kQePh6UTB90.pt-BR.vtt
4.4 kB
Part 14-Module 01-Lesson 05_Analyzing Results/13. Multiple Metrics Example-60IGcSho56o.pt-BR.vtt
4.4 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-ycbXO4xBEVw.en.vtt
4.4 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/22. L2 09 Lists And Membership Operators V2-rNV_E50wcWM.pt-BR.vtt
4.4 kB
Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules-jPGyFgcIvsM.en.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/20. Plotting With Pandas-kR7KZFqciFE.ar.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-Zdl01HMSjTw.pt-BR.vtt
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Part 15-Module 01-Lesson 02_Design Principles/img/lie-factor.png
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/index.html
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/index.html
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/04. Element-wise Matrix Operations-vjUykZyzko4.pt-BR.vtt
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Part 10-Module 01-Lesson 03_Udacity Professional Profile/index.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/02. Defining Data Visualization-TMH43G11OnQ.ar.vtt
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Part 12-Module 02-Lesson 01_Introduction and Efficiency/10. Worst Case and Approximation-ZYcmui02J40.pt-BR.vtt
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/index.html
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/06. CSV Format-ra93hy88cok.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/33. Highlight Countries-bq_gVndUj1U.pt-BR.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/19. Sizing Triggering-ae9SWJxGM0w.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size-MLzRdgcFYQQ.en.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/24. Lessons Learned-GonjL0GbNiw.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-wPI9WOfpZbM.ar.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/07. History of AB Testing-NNiKGao0xnk.en.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.ar.vtt
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Part 12-Module 02-Lesson 06_Graphs/index.html
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.ar.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/06. Aggregation Operators 1-mRNyMEoCoY0.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-jkJ4dbbpVCQ.ar.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/26. Updates-mpMHJQalRck.ar.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/11. Dummy Variable Interpretation-TxP_TD0kbOo.en.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -exMGBx6Rs_E.ar.vtt
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Part 21-Module 01-Lesson 05_Scripting/13. Handling Errors Try Except Finally-S6hwBZG0KwM.ar.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/06. Why Do Analysts Like SQL-uCNOtUht2Xc.ar.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/22. Why Do Analysts Like SQL-uCNOtUht2Xc.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-uoHzcmf4yXU.en-US.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/34. Completing the Update Function-lUYD6lldDeU.zh-CN.vtt
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Part 09-Module 01-Lesson 02_R Basics/04. Install RStudio on Windows-5ZbjUEg4a1g.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/53. Inspecting Accessor Functions-bRkkMdkkFQw.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-uoHzcmf4yXU.en.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/14. What is the Question-xQJyObqxg3E.pt-BR.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/13. Multiple Metrics Example-60IGcSho56o.en.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/08. Calculating Correlation-yLql7kR_6GE.ar.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/08. Calculating Correlation-yLql7kR_6GE.ar.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/11. Cleaning For Tidiness -6nMKFhpVCRU.ar.vtt
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Part 15-Module 01-Lesson 04_Telling Stories with Tableau/02. Exploring data with Trina-sLzULEjMY1E.en.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/16. Sizing Overview-sKRWt_iS7zo.ar.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-OurfO1ZR2GU.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/10. Techniques to Gather Additional Data-6mTsvU0ML94.en.vtt
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/05. Iterating through Ways Tags-GYhOEJ8EXkg.zh-CN.vtt
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/06. Iterating through Ways Tags-GYhOEJ8EXkg.zh-CN.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/14. Other JOINs-4edRxFmWUEw.en.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/08. Números inteiros e floats-MiJ1vfWp-Ts.zh-CN.vtt
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Part 05-Module 01-Lesson 05_Data Quality/15. Auditing Completeness-PMbcv9AYQT4.en.vtt
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Part 04-Module 01-Lesson 02_Jupyter notebooks/index.html
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Part 06-Module 01-Lesson 03_Analyzing Data/04. The Aggregation Pipeline-0sl_mbV-fho.zh-CN.vtt
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Part 16-Module 01-Lesson 02_Jupyter notebooks/index.html
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/16. Data Types-ZqRIS9etBqY.pt-BR.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/04. Data Types - Data Visualization and D3.js-ZqRIS9etBqY.pt-BR.vtt
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Part 09-Module 01-Lesson 01_What is EDA/03. Why learn EDA-YM68DrqJw1I.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/08. Declaring Relationships-1FjqstT1faI.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/17. Summary Metrics Example--DqU-ARfQr4.en.vtt
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Part 19-Module 01-Lesson 02_Design/09. Design Integrity-y72_fVFtqlY.pt-BR.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/13. Population vs. Cohort-HC2dunMuVW4.ar.vtt
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/04. Element-wise Matrix Operations-vjUykZyzko4.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/19. Viewer-driven Examples-ft07qc8rTwM.ar.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/10. Details of the Data Science Process-8TeiMKUmoYQ.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/08. Unit of Analysis vs. Unit of Diversion-rzim0wu_0kM.ar.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-dtnjREsGfXI.ar.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import-tU1N-8aNB_M.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/03. The Benefits of Interactivity-fIIyFYQyGLk.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data-8FD_iOP24UA.ar.vtt
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Part 12-Module 02-Lesson 02_List-Based Collections/03. Arrays-OnPP5xDmFv0.pt-BR.vtt
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Part 05-Module 01-Lesson 05_Data Quality/19. More About Correcting Data-vWBMgSQvsVk.ar.vtt
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Part 19-Module 01-Lesson 02_Design/13. Using Color-6bAedqD3ilw.zh-CN.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/20. Practical, or Substantive, Significance-Q576t5aaZ34.en.vtt
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Part 14-Module 01-Lesson 06_Final Project/index.html
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/14. Adding a DataFrame to a Series-K2sUmPodhqg.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-FORb9Tja-p0.en-US.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/14. Adding a DataFrame to a Series-K2sUmPodhqg.en.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/06. Flexible Schema-6a-YgbrEACk.pt-BR.vtt
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Part 12-Module 01-Lesson 02_Practice Behavioral Questions/index.html
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Part 12-Module 01-Lesson 05_Interview Practice/04. Query a SQL database-UVSFLWdAKl4.zh-CN.vtt
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Part 09-Module 01-Lesson 02_R Basics/12. Factor Variables-0bkvt4KEqjE.ar.vtt
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Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-FORb9Tja-p0.en.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/13. Where's the Data-rHQ8z4fIthA.ar.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/06. Collisions-BUaWIjZ_ToY.en-US.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/26. DATE Functions Part II-UPWkDhW4cLI.pt-BR.vtt
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Part 19-Module 01-Lesson 02_Design/09. Design Integrity-y72_fVFtqlY.en.vtt
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Part 12-Module 02-Lesson 01_Introduction and Efficiency/index.html
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Part 12-Module 02-Lesson 04_Maps and Hashing/06. Collisions-BUaWIjZ_ToY.en.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/05. NumPy and Pandas Data Types-seEFuJ-qvlg.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/05. NumPy and Pandas Data Types-seEFuJ-qvlg.pt-BR.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/11. Dummy Variable Interpretation-TxP_TD0kbOo.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5DvUOwA7xhU.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/17. Different Types of Narrative Structures-vTlpDo33ezg.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/31. Data Join with a Key Function-ue_TULswM1Y.ar.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/08. Report Results-xNbzHOnSx5Q.en.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/26. DATE Functions Part II-UPWkDhW4cLI.en.vtt
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Part 12-Module 02-Lesson 02_List-Based Collections/index.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/01. Introduction to Course-gR_buSP6sdw.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/17. Sizing Example-f69Hs7m1axc.pt-BR.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/17. Drawing Conclusions-CZQ-nZyUG7g.pt-BR.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/20. Notation for Random Variables-8NxTW1u4s-Y.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/05. Intro to CSVs-UFiJYYPL95g.ar.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/01. Independent Samples-K25Xtqr2WvI.zh-CN.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/09. Metric Choice-BeIy4A6YKrY.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/16. Data Types-ZqRIS9etBqY.en.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/04. Data Types - Data Visualization and D3.js-ZqRIS9etBqY.en.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/19. What Is A P-value Anyway-eU6pUZjqviA.pt-BR.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment Solution-H50mPHHp6fY.ar.vtt
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Part 19-Module 01-Lesson 02_Design/03. Exploratory vs. Explanatory Analysis-wvgBSMks4p8.pt-BR.vtt
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Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-FDSmlIBy7ko.ja.vtt
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Part 12-Module 02-Lesson 05_Trees/06. Depth-First Traversals-wp5ohHFTieM.en-US.vtt
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Part 12-Module 02-Lesson 05_Trees/06. Depth-First Traversals-wp5ohHFTieM.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/08. Report Results-xNbzHOnSx5Q.pt-BR.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/05. Brainstorming-LJFYhMDCCsU.zh-CN.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts-zbjRiYSSR_Y.ar.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/02. Why Use Separate Tables-UIQBtpmqYOs.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/19. Extracting Information from sklearn-zDIRQE_oxfk.pt-BR.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/10. Inter- vs. Intra-User Experiments-EGE8ddtWIeo.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/12. Drawing and Altering the Map-soflPyVhb6o.ar.vtt
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Part 11-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary-gBwGPI0srBE.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/17. Summary Metrics Example--DqU-ARfQr4.pt-BR.vtt
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Part 03-Module 01-Lesson 21_PS 8a Estimation/index.html
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Part 14-Module 01-Lesson 05_Analyzing Results/08. Single Metric Introduction-StP9L9f70EU.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/33. Highlight Countries-bq_gVndUj1U.en.vtt
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Part 21-Module 01-Lesson 05_Scripting/27. Experimenting With An Interpreter-hspPtnQwMPg.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/23. PCA for Feature Transformation-8kUPRUEMCA8.en.vtt
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Part 15-Module 01-Lesson 04_Telling Stories with Tableau/02. Exploring data with Trina-sLzULEjMY1E.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/15. Extracting Entities-aJD8WJa3-9A.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -Y288CGrwGy4.ar.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-28iU6GrDVfU.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/28. Joins in D3-rDjOINfKftY.pt-BR.vtt
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Part 21-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.ar.vtt
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Part 21-Module 01-Lesson 05_Scripting/06. Programming Environment Setup-EKxDnCK0NAk.en.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. More on Performance Tuning-ZK1FvNH10Ag.ar.vtt
4.2 kB
Part 13-Module 01-Lesson 04_Design Principles/19. Pre-attentive Attributes-6UvLbIX0NQ4.ar.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/03. Normalized Design Part Two-l6SDnhM7B_k.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/21. Lada's Money Bag Meme-Isa_FGQrvgs.pt-BR.vtt
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Part 09-Module 02-Lesson 01_Explore and Summarize Data/index.html
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Part 05-Module 02-Lesson 01_Data and Tables/10. How Queries Happen-v3EkXogyIL4.ar.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/05. Brainstorming-LJFYhMDCCsU.pt-BR.vtt
4.2 kB
Part 21-Module 01-Lesson 03_Control Flow/31. List Comprehensions-6qxo-NV9v_s.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/19. Extracting Information from sklearn-zDIRQE_oxfk.en-US.vtt
4.2 kB
Part 12-Module 02-Lesson 02_List-Based Collections/06. Linked Lists in Depth-ZONGA5wmREI.en-US.vtt
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Part 04-Module 03-Lesson 01_Investigate a Dataset/index.html
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Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/13. Scott's Advice to Break into Data Vis-v5ywQMRCxMg.zh-CN.vtt
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Part 15-Module 01-Lesson 04_Telling Stories with Tableau/index.html
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Part 12-Module 02-Lesson 02_List-Based Collections/06. Linked Lists in Depth-ZONGA5wmREI.en.vtt
4.2 kB
Part 21-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/19. Extracting Information from sklearn-zDIRQE_oxfk.en.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/22. NEW D3 Scale Syntax-nqi4oT2aeAw.en-US.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/04. The New Journalism-ub1_Gwc6wN8.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/22. NEW D3 Scale Syntax-nqi4oT2aeAw.en.vtt
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Part 09-Module 01-Lesson 01_What is EDA/index.html
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Part 12-Module 02-Lesson 03_Searching and Sorting/14. Efficiency of Quick Sort-aMb5GHPGQ1U.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/14. Loading Data with Nested Functions-ME6F4Nyjv8o.ar.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/07. History of AB Testing-NNiKGao0xnk.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-w6CLWh1dLCU.en.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/06. Flexible Schema-6a-YgbrEACk.en.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/17. Shape of Distributions-UnN99AAYf8k.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/14. Population vs. Cohort Example-MXukXfzL59E.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-9JfaMZcSlQA.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/09. Inspecting Variables and Data-eA8i6-n-Vc4.en.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/10. Single Metric Gotchas-WrfWFLiFeMU.en.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/13. Interview with Art - Part 3-M6PKr3S1rPg.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/11. Other Techniques Example-sOGuF3it6Ek.pt-BR.vtt
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/index.html
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Part 13-Module 01-Lesson 08_Animation and Interaction/02. Case Study US Unemployment-R6Nk8NsEzUA.en-US.vtt
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Part 11-Module 01-Lesson 14_Validation/03. TrainTest Split in sklearn-lSwvUmZCvco.en.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/12. Target Population Example-kEFp6xIb8cs.ar.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/25. Correlation Does Not Imply Causation-aeEhfjPFiCw.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/48. Matt's Tips for Making Maps-HCYCT2TXhAM.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/02. Case Study US Unemployment-R6Nk8NsEzUA.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import-tU1N-8aNB_M.en.vtt
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/02. Cleaning with String Functions-y1fduSu7Ovc.ar.vtt
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Part 03-Module 01-Lesson 15_PS 5b Additional Practice (Optional)/index.html
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Part 12-Module 02-Lesson 06_Graphs/02. What Is a Graph-p-_DFOyEMV8.en-US.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/02. Unit of Diversion Overview-Gh32VbXrmdQ.ar.vtt
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Part 03-Module 01-Lesson 24_PS 9a Hypothesis Testing/index.html
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Part 12-Module 02-Lesson 06_Graphs/02. What Is a Graph-p-_DFOyEMV8.en.vtt
4.2 kB
Part 17-Module 01-Lesson 08_Python Probability Practice/index.html
4.2 kB
Part 12-Module 02-Lesson 04_Maps and Hashing/index.html
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Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-0L3Obq4FSVQ.zh-CN.vtt
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Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-TIgfjmp-4BA.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/05. NumPy and Pandas Data Types-seEFuJ-qvlg.en.vtt
4.2 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/05. NumPy and Pandas Data Types-seEFuJ-qvlg.en.vtt
4.2 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/45. Fixing the Buttons-NxM_iu4sDxw.ar.vtt
4.2 kB
Part 11-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter-m2a2K4lprQw.ar.vtt
4.2 kB
Part 11-Module 01-Lesson 07_Regressions/31. R Squared in SKlearn-Dxf1I4IE6co.zh-CN.vtt
4.2 kB
Part 12-Module 02-Lesson 03_Searching and Sorting/14. Efficiency of Quick Sort-aMb5GHPGQ1U.pt-BR.vtt
4.2 kB
Part 11-Module 01-Lesson 12_Feature Selection/14. Balancing Error with Number of Features-IwiIFMcDwoA.en.vtt
4.2 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/22. Looking at Samples of Households-kQePh6UTB90.en.vtt
4.2 kB
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.ar.vtt
4.2 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-28iU6GrDVfU.pt-BR.vtt
4.2 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/06. Choosing Metrics-eAukkpVFl5c.pt-BR.vtt
4.2 kB
Part 14-Module 01-Lesson 05_Analyzing Results/03. Choosing Invariants-E1ePfjcVH3I.en.vtt
4.2 kB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/08. Notation Intro-xHwIU4j3gBc.en-US.vtt
4.2 kB
Part 12-Module 02-Lesson 03_Searching and Sorting/07. Bubble Sort-h_osLG3GmjE.en-US.vtt
4.2 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/14. Population vs. Cohort Example-MXukXfzL59E.en.vtt
4.2 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/19. What Is A P-value Anyway-eU6pUZjqviA.en.vtt
4.2 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/10. Boolean Comparison and Logical Operators-iNNsUJIDtVU.ar.vtt
4.2 kB
Part 09-Module 01-Lesson 01_What is EDA/08. Aude Explores Coordinated Migration-7ihp6ofAJG8.zh-CN.vtt
4.2 kB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/08. Notation Intro-xHwIU4j3gBc.en.vtt
4.2 kB
Part 12-Module 02-Lesson 03_Searching and Sorting/07. Bubble Sort-h_osLG3GmjE.en.vtt
4.2 kB
Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-paj5z9U1OBk.ar.vtt
4.1 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-w6CLWh1dLCU.pt-BR.vtt
4.1 kB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/03. Your First Subquery-cTM1jPYXLoQ.ar.vtt
4.1 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/15. Extracting Entities-aJD8WJa3-9A.zh-CN.vtt
4.1 kB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/index.html
4.1 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/10. Inter- vs. Intra-User Experiments-EGE8ddtWIeo.en.vtt
4.1 kB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/08. Notation Intro-xHwIU4j3gBc.pt-BR.vtt
4.1 kB
Part 13-Module 01-Lesson 07_Narrative Structures/13. Errors in Data Collection-xcYDjXpYbs0.pt-BR.vtt
4.1 kB
Part 17-Module 01-Lesson 13_Case Study AB tests/07. Metric - Click Through Rate-EpfoKAwV_Eg.pt-BR.vtt
4.1 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/20. How Scales Work-4zqm8dz7Z-k.zh-CN.vtt
4.1 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/30. Code Structure and JavaScript-vPCDvEOjP7c.ar.vtt
4.1 kB
Part 13-Module 01-Lesson 05_Dimple.js/09. Inspecting Variables and Data-eA8i6-n-Vc4.pt-BR.vtt
4.1 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 2-W2tL3QSBi3k.zh-CN.vtt
4.1 kB
Part 09-Module 01-Lesson 03_Explore One Variable/21. Lada's Money Bag Meme-Isa_FGQrvgs.en.vtt
4.1 kB
Part 12-Module 02-Lesson 02_List-Based Collections/03. Arrays-OnPP5xDmFv0.en-US.vtt
4.1 kB
Part 14-Module 01-Lesson 05_Analyzing Results/10. Single Metric Gotchas-WrfWFLiFeMU.pt-BR.vtt
4.1 kB
Part 12-Module 02-Lesson 02_List-Based Collections/03. Arrays-OnPP5xDmFv0.en.vtt
4.1 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/06. Choosing Metrics-eAukkpVFl5c.en.vtt
4.1 kB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/14. What is the Question-xQJyObqxg3E.en.vtt
4.1 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-BqQbAqok8JU.ar.vtt
4.1 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-BqQbAqok8JU.ar.vtt
4.1 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/26. Confidence Interval Case Breakdown-6pGDwrJHitw.pt-BR.vtt
4.1 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-74mudn321tA.pt-BR.vtt
4.1 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-28iU6GrDVfU.ja.vtt
4.1 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/09. Questions and Consent-ZmXg42IoG_Q.ar.vtt
4.1 kB
Part 05-Module 02-Lesson 01_Data and Tables/02. What's a Database - Intro to Relational Databases-V4gbPVdUOpw.ar.vtt
4.1 kB
Part 12-Module 02-Lesson 08_Technical Interview - Python/09. Debugging-Bz1tlvkql9Q.en-US.vtt
4.1 kB
Part 12-Module 02-Lesson 08_Technical Interview - Python/09. Debugging-Bz1tlvkql9Q.en.vtt
4.1 kB
Part 04-Module 01-Lesson 01_Anaconda/index.html
4.1 kB
Part 16-Module 01-Lesson 01_Anaconda/index.html
4.1 kB
Part 07-Module 01-Lesson 01_GitHub Review/04. Interview with Art - Part 1-ClLYamtaO-Q.pt-BR.vtt
4.1 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/01. Introduction-yod62-mxXR4.ar.vtt
4.1 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/21. Variability-1KmFcGt6Uo0.ar.vtt
4.1 kB
Part 21-Module 01-Lesson 03_Control Flow/02. If Statements-jWiIUMrwPqA.ar.vtt
4.1 kB
Part 11-Module 01-Lesson 07_Regressions/27. Problem with Minimizing Absolute Errors-U46D7oEijlI.en.vtt
4.1 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-5GYA5j1fqBU.ar.vtt
4.1 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/07. What is a Projection-QjVNXfI8YRk.zh-CN.vtt
4.1 kB
Part 03-Module 01-Lesson 32_PS 11b Additional Practice (Optional)/index.html
4.1 kB
Part 17-Module 01-Lesson 08_Python Probability Practice/04. Simulating Many Coin Flips-AqpWQIj2V5Y.ar.vtt
4.1 kB
Part 18-Module 03-Lesson 01_Assessing Data/06. Types vs. Steps -oZmndg-BnPk.ar.vtt
4.1 kB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.ar.vtt
4.1 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.ar.vtt
4.1 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-iJEBxsKDDoE.ar.vtt
4.1 kB
Part 16-Module 03-Lesson 03_SQL Aggregations/13. GROUP BY-9vb67TF4WV0.ar.vtt
4.1 kB
Part 12-Module 02-Lesson 02_List-Based Collections/06. Linked Lists in Depth-ZONGA5wmREI.pt-BR.vtt
4.1 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-qsWz7r8muII.en-US.vtt
4.1 kB
Part 13-Module 01-Lesson 07_Narrative Structures/38. Communicating Your Message-wZt6fXEUqQM.en.vtt
4.1 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-qsWz7r8muII.en.vtt
4.1 kB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/04. Element-wise Matrix Operations-vjUykZyzko4.zh-CN.vtt
4.1 kB
Part 13-Module 01-Lesson 05_Dimple.js/34. Summary of Dimple and Chart Types-OrdADko3k1Q.ar.vtt
4.1 kB
Part 13-Module 01-Lesson 07_Narrative Structures/46. Inspecting Data with Functions--itFNdnc5ns.zh-CN.vtt
4.1 kB
Part 11-Module 01-Lesson 09_Clustering/02. Clustering Movies-g8PKffm8IRY.ar.vtt
4.1 kB
Part 09-Module 01-Lesson 03_Explore One Variable/21. Lada's Money Bag Meme-Isa_FGQrvgs.ja.vtt
4.1 kB
Part 13-Module 01-Lesson 07_Narrative Structures/56. Recap and Data Dependency-00Tz_3_91RU.ar.vtt
4.1 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/08. Whitespace-UxkIwcOczQQ.ar.vtt
4.1 kB
Part 13-Module 01-Lesson 07_Narrative Structures/03. Correlation vs Causation-8u96-UEf_ms.ar.vtt
4.1 kB
Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-FDSmlIBy7ko.pt-BR.vtt
4.0 kB
Part 13-Module 01-Lesson 05_Dimple.js/29. From Bars to Circles to Lines-MA-n0Hi3Wyg.pt-BR.vtt
4.0 kB
Part 09-Module 01-Lesson 01_What is EDA/05. Goals of EDA-NEvuulahg2g.ar.vtt
4.0 kB
Part 13-Module 01-Lesson 07_Narrative Structures/21. Drone Strikes and Gun Deaths-_MXW29cfh_8.ar.vtt
4.0 kB
Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment Solution-LhdGQC_vjEs.ar.vtt
4.0 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-GXT_vXBA0vQ.ja.vtt
4.0 kB
Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-krV6r7HxmZU.ja.vtt
4.0 kB
Part 05-Module 02-Lesson 01_Data and Tables/15. Joining Tables-lXoiI0gx3MU.pt-BR.vtt
4.0 kB
Part 21-Module 01-Lesson 03_Control Flow/25. Break and Continue-F6qJAv9ts9Y.en.vtt
4.0 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/16. Assess Programmatic-6JubHCD7dh4.ar.vtt
4.0 kB
Part 03-Module 01-Lesson 22_PS 8b Additional Practice (Optional)/index.html
4.0 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/03. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.ar.vtt
4.0 kB
Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-DxCwtkrYR-s.ar.vtt
4.0 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/17. Aggregations-4nGL3y3Nq-0.ar.vtt
4.0 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/04. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.ar.vtt
4.0 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-8zWQmAVPthY.en.vtt
4.0 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/13. Pandas Series-8zWQmAVPthY.en.vtt
4.0 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-hmhlyOVAVOs.ar.vtt
4.0 kB
Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules-jPGyFgcIvsM.zh-CN.vtt
4.0 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/08. Standard Deviation Calculation-H5zA1A-XPoY.pt-BR.vtt
4.0 kB
Part 07-Module 01-Lesson 01_GitHub Review/02. GitHub profile important items-prvPVTjVkwQ.ar.vtt
4.0 kB
Part 21-Module 01-Lesson 05_Scripting/06. Programming Environment Setup-EKxDnCK0NAk.zh-CN.vtt
4.0 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/06. CSVs in Python-YIDH9HBY3Qk.ar.vtt
4.0 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-8zWQmAVPthY.pt-BR.vtt
4.0 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/13. Pandas Series-8zWQmAVPthY.pt-BR.vtt
4.0 kB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/03. Iterative Parsing-pxUvIP4PQt0.ar.vtt
4.0 kB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/03. Iterative Parsing-pxUvIP4PQt0.ar.vtt
4.0 kB
Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-CPDMSJEH16s.pt-BR.vtt
4.0 kB
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-HEnJRwJ23us.ar.vtt
4.0 kB
Part 13-Module 01-Lesson 07_Narrative Structures/38. Communicating Your Message-wZt6fXEUqQM.pt-BR.vtt
4.0 kB
Part 03-Module 01-Lesson 20_L8 Estimation/23. CI Bounds-6MdZ5NUfen0.pt-BR.vtt
4.0 kB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-c-v-Xa_R4SA.pt-BR.vtt
4.0 kB
Part 13-Module 01-Lesson 05_Dimple.js/20. Object Oriented Design and Charts-2uzNpGWdavc.ar.vtt
4.0 kB
Part 18-Module 03-Lesson 01_Assessing Data/14. Programatic Assessment -Bk_Ve3-4eps.ar.vtt
4.0 kB
Part 13-Module 01-Lesson 07_Narrative Structures/28. Joins in D3-rDjOINfKftY.en.vtt
4.0 kB
Part 13-Module 01-Lesson 04_Design Principles/25. Communicating with Color-QnFtYKXf7TQ.ar.vtt
4.0 kB
Part 15-Module 01-Lesson 02_Design Principles/13. Communicating with Color-QnFtYKXf7TQ.ar.vtt
4.0 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax-7XyFjPDPoZQ.ar.vtt
4.0 kB
Part 11-Module 01-Lesson 06_Datasets and Questions/02. What Is A POI-wDQhif-MWuY.en.vtt
4.0 kB
Part 05-Module 02-Lesson 05_Deeper into SQL/03. Normalized Design Part Two-l6SDnhM7B_k.en.vtt
4.0 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/17. Range Queries-6r5Xc-_lhEI.pt-BR.vtt
4.0 kB
Part 17-Module 01-Lesson 08_Python Probability Practice/02. Simulating Coin Flips-7YtQNZ3iy6o.pt-BR.vtt
4.0 kB
Part 13-Module 01-Lesson 07_Narrative Structures/04. The New Journalism-ub1_Gwc6wN8.en.vtt
4.0 kB
Part 05-Module 01-Lesson 06_Problem Set Data Quality/index.html
4.0 kB
Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-9JfaMZcSlQA.en.vtt
4.0 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/17. Sizing Example-f69Hs7m1axc.en.vtt
4.0 kB
Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-bR7EoKjN0EM.ar.vtt
4.0 kB
Part 13-Module 01-Lesson 04_Design Principles/22. Encoding Nothing-6bpET1lWVtA.ar.vtt
4.0 kB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/05. 03 Tableau Interface-q3E4CCYeIyM.en.vtt
4.0 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/23. Drawing Conclusions Example-yAl58ccwyvU.ar.vtt
4.0 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/04. 29 Number Summary-gzUN5zKLHjQ.pt-BR.vtt
4.0 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/22. Comparing the Two Student Groups-6UYEM0XUSGQ.zh-CN.vtt
4.0 kB
Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-YZb-Uam-Ics.ar.vtt
4.0 kB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/08. Exact and Approximate Algorithms-3A8YqOYlAwQ.pt-BR.vtt
4.0 kB
Part 13-Module 01-Lesson 07_Narrative Structures/61. I am Legend-EdiM9XCqc0Y.ar.vtt
4.0 kB
Part 11-Module 01-Lesson 02_Naive Bayes/36. Naive Bayes Strengths and Weaknesses-nfbKTrufPOs.ar.vtt
4.0 kB
Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-krV6r7HxmZU.pt-BR.vtt
4.0 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/02. Course Format-rVmwPGFtk_Y.ar.vtt
4.0 kB
Part 03-Module 01-Lesson 11_L4 Variability/32. SD Social Networkers-cy8BwWl36Q4.zh-CN.vtt
4.0 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size-MLzRdgcFYQQ.zh-CN.vtt
4.0 kB
Part 17-Module 01-Lesson 05_Binomial Distribution/16. Binomial Distribution Conclusion-9gjCYs8f_PU.ar.vtt
4.0 kB
Part 05-Module 01-Lesson 04_Problem Set Data in More Complex Formats/index.html
4.0 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/13. Binomial Distribution-PVTChqpnr5Q.ar.vtt
4.0 kB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/08. Exact and Approximate Algorithms-3A8YqOYlAwQ.en-US.vtt
4.0 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/13. Worksheets-2xRKvQTRtlk.pt-BR.vtt
4.0 kB
Part 11-Module 01-Lesson 11_Text Learning/11. Stemming with NLTK-gWbkW_cyNs8.en.vtt
4.0 kB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML Structure-UjCbXQ8Coic.pt-BR.vtt
4.0 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/36. Groups And Sets-Yb-91NVNgTA.zh-CN.vtt
4.0 kB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/08. Exact and Approximate Algorithms-3A8YqOYlAwQ.en.vtt
4.0 kB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/11. CAST-LbyOq4ofLng.ar.vtt
4.0 kB
Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-FORb9Tja-p0.zh-CN.vtt
4.0 kB
Part 21-Module 01-Lesson 05_Scripting/08. Scripting With Raw Input-Fs9uLV2qfgI.ar.vtt
4.0 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/29. Data Analysis and Related Terms-9g9_tlhbNSw.ar.vtt
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Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-PZSPhQCVABg.ar.vtt
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Part 12-Module 02-Lesson 01_Introduction and Efficiency/10. Worst Case and Approximation-ZYcmui02J40.zh-CN.vtt
4.0 kB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML Structure-UjCbXQ8Coic.en.vtt
4.0 kB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/04. Statistical Significance-kpdwHL54eys.en.vtt
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Part 11-Module 01-Lesson 14_Validation/09. K-Fold CV in sklearn-QSYMwFbE7PA.en-US.vtt
4.0 kB
Part 05-Module 03-Lesson 01_Wrangle OpenStreetMap Data/index.html
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Part 11-Module 01-Lesson 14_Validation/09. K-Fold CV in sklearn-QSYMwFbE7PA.en.vtt
4.0 kB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/07. Efficiency-I-RASDPbDrI.pt-BR.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/11. Gotchas Simpson’s Paradox-GSPTcqNpab8.en.vtt
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Part 08-Module 01-Lesson 01_Conduct a Job Search/index.html
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Part 18-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty Messy -WG6mil60jq0.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/40. Smoothing the Animation with Transitions-9c8he26k_iY.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.ar.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 Solution-kqcuw1qCLEM.ar.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/39. Using extent() for scales-oazLw2JhKiU.ar.vtt
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Part 12-Module 02-Lesson 06_Graphs/02. What Is a Graph-p-_DFOyEMV8.pt-BR.vtt
3.9 kB
Part 13-Module 01-Lesson 05_Dimple.js/30. EDA vs Sketching Data Visualizations-hFlVFyatBF0.zh-CN.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/06. Collisions-BUaWIjZ_ToY.pt-BR.vtt
3.9 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/20. Regex Operator-MbJfmI7kzQI.pt-BR.vtt
3.9 kB
Part 11-Module 01-Lesson 06_Datasets and Questions/02. What Is A POI-wDQhif-MWuY.pt-BR.vtt
3.9 kB
Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-oEhevl5DWpk.en.vtt
3.9 kB
Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-CPDMSJEH16s.en.vtt
3.9 kB
Part 13-Module 02-Lesson 01_Make Effective Data Visualization/index.html
3.9 kB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/02. Standard Error-GTsnxTCjmcM.zh-CN.vtt
3.9 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/25. L2 06 Lists Methods V1-tz2Ja1Eaeqo.zh-CN.vtt
3.9 kB
Part 12-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier-Uy89Ff49pRc.zh-CN.vtt
3.9 kB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/04. Meet the Careers Team-cuKecPpZ7PM.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/03. Data Analysis Process-cAceF0h4vpI.zh-CN.vtt
3.9 kB
Part 16-Module 03-Lesson 03_SQL Aggregations/26. DATE Functions Part II-UPWkDhW4cLI.zh-CN.vtt
3.9 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/23. Marks And Filters-FeYRmZHHu0A.ar.vtt
3.9 kB
Part 11-Module 01-Lesson 12_Feature Selection/14. Balancing Error with Number of Features-IwiIFMcDwoA.pt-BR.vtt
3.9 kB
Part 11-Module 02-Lesson 01_Identify Fraud from Enron Email/index.html
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/05. 03 Tableau Interface-q3E4CCYeIyM.zh-CN.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/13. Worksheets-2xRKvQTRtlk.en.vtt
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Part 10-Module 01-Lesson 02_LinkedIn Review/index.html
3.9 kB
Part 02-Module 02-Lesson 01_Project Prep/index.html
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/04. Ways in the Open Street Map XML-1OwIbj9dcLo.ar.vtt
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/05. Ways in the Open Street Map XML-1OwIbj9dcLo.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-ycbXO4xBEVw.zh-CN.vtt
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Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-YbVuN2KOlt4.pt-BR.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-oEhevl5DWpk.pt-BR.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/04. Interview with Art - Part 1-ClLYamtaO-Q.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-K6zJtrTEf6k.ar.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/15. What About More Than Two Variables -ufKcdUbLj9c.ar.vtt
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Part 03-Module 02-Lesson 01_Test a Perceptual Phenomenon/index.html
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Part 14-Module 01-Lesson 01_Overview of AB Testing/06. Other Techniques-KsiyW6bPux8.ar.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/13. Getting Data into MongoDB-hi6g1NE3sPk.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-MlE3BuOvWnU.pt-BR.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/10. NumPy Index Arrays-MlE3BuOvWnU.pt-BR.vtt
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Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-FDSmlIBy7ko.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.ar.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/01. Intro-UJyJm79RS88.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/13. Errors in Data Collection-xcYDjXpYbs0.en.vtt
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/08. 05 Hierarchies-vkHeQcI08yc.en.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/20. Hierarchies-wl_AM-spH68.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-JqyUT7RbvgI.ar.vtt
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Part 21-Module 01-Lesson 05_Scripting/27. Experimenting With An Interpreter-hspPtnQwMPg.en.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/04. Algorithm Options-S-cGZ-FEdjQ.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-krV6r7HxmZU.en.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/19. Exists-j5l5UvE3Odw.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-uoHzcmf4yXU.zh-CN.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/14. Other JOINs-4edRxFmWUEw.pt-BR.vtt
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Part 09-Module 01-Lesson 01_What is EDA/03. Why learn EDA-YM68DrqJw1I.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/22. Looking at Samples of Households-kQePh6UTB90.ja.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/14. Other JOINs-4edRxFmWUEw.zh-CN.vtt
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Part 19-Module 01-Lesson 02_Design/09. Design Integrity-y72_fVFtqlY.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5DvUOwA7xhU.zh-CN.vtt
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Part 12-Module 01-Lesson 03_Interview Fails/index.html
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Part 14-Module 01-Lesson 05_Analyzing Results/17. Drawing Conclusions-CZQ-nZyUG7g.zh-CN.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/19. Exists-j5l5UvE3Odw.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/12. Related Tables-lMwSjDYgCq0.pt-BR.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/11. Dummy Variable Interpretation-TxP_TD0kbOo.zh-CN.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/02. Sanity Checks-OVnlC_T3EpI.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/63. Adding Text to the Legend-VPI9MVqGiSM.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/07. How to Lie with Bar Charts-75c7a4R4pZ0.zh-CN.vtt
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assets/css/fonts/KaTeX_Size3-Regular.woff2
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Part 14-Module 01-Lesson 01_Overview of AB Testing/26. Confidence Interval Case Breakdown-6pGDwrJHitw.en.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/31. L2 02 Dictionaries And Identiy Operators V3-QR8HTxCTWi0.pt-BR.vtt
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assets/css/styles.css
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Part 12-Module 02-Lesson 05_Trees/06. Depth-First Traversals-wp5ohHFTieM.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/15. Joining Tables-lXoiI0gx3MU.en.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/22. Interactions Higher Order Terms-gMHwogzqPOk.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/31. Customizing a Dimple Chart-93MgOnKP5m0.ar.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/20. Hierarchies-wl_AM-spH68.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/02. Case Study US Unemployment-R6Nk8NsEzUA.pt-BR.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/13. Multiple Metrics Example-60IGcSho56o.zh-CN.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/08. Addressing Missing Data First -ArAGZCUMj9Q.ar.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/18. Debugging Data Analysis Code -l1pZZKsESAc.en.vtt
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Part 19-Module 01-Lesson 02_Design/15. Shape, Size, and other Tools-fzEliHW3ZLM.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-vsLtePFaOFY.ar.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-vsLtePFaOFY.ar.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/14. Adding a DataFrame to a Series-K2sUmPodhqg.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/14. Adding a DataFrame to a Series-K2sUmPodhqg.zh-CN.vtt
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Part 12-Module 02-Lesson 05_Trees/06. Depth-First Traversals-wp5ohHFTieM.zh-CN.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/12. Target Population Example-XsyavvSGjLM.pt-BR.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1-mUfrDUEEa_k.pt-BR.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/06. Flexible Schema-6a-YgbrEACk.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-AaLIKufl_mY.ar.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/04. Why MongoDB-jjMw4Ju-1CM.ar.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/19. Plotting for DataFrames-CDVgPA0Mv2o.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/19. Plotting for DataFrames-CDVgPA0Mv2o.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/27. Problem with Minimizing Absolute Errors-U46D7oEijlI.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/23. Making Histograms-0J5lNTGbspg.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/29. Formula for Location of Median-lNYLU1b4qoM.pt-BR.vtt
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/16. Type And Quality Plot - Part 1-iRCS1sE78KI.ar.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/26. Predicting Based on Many Features-oZqGlJbRZu4.ar.vtt
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Part 11-Module 01-Lesson 14_Validation/09. K-Fold CV in sklearn-QSYMwFbE7PA.pt-BR.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/11. Other Techniques Example-sOGuF3it6Ek.en.vtt
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Part 03-Module 01-Lesson 25_PS 9b Additional Practice (Optional)/index.html
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Part 11-Module 01-Lesson 01_Welcome to Machine Learning/index.html
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Part 06-Module 01-Lesson 01_Working with MongoDB/17. Range Queries-6r5Xc-_lhEI.en.vtt
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Part 21-Module 01-Lesson 05_Scripting/26. Third Party Libraries And Package Managers-epOze9gC6T4.pt-BR.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/20. Clean Define-qHB4jsqcfi4.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/13. Uniqueness and Keys-TIayTr4y9RA.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-c-v-Xa_R4SA.en-US.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-c-v-Xa_R4SA.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import-tU1N-8aNB_M.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-Zdl01HMSjTw.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/07. Small Multiples-HS_dsOQfwz8.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge-DMhldSg2_vs.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/47. Discovery versus Presentation-znQ3iBhhJtA.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/17. Summary Metrics Example--DqU-ARfQr4.zh-CN.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment -BNRJdhA8_s8.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/34. Comparing Classification and Regression-G_0W912qmGc.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/02. Approaches to Journalism-AxFSDfKP7Zs.zh-CN.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/06. Aggregation Operators 1-mRNyMEoCoY0.zh-CN.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/06. Collisions-BUaWIjZ_ToY.zh-CN.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/08. Overview of Business Example-tlSe7H9BDy8.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data-x2dmBUEKQIA.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/23. Nonparametric Answers-Z0QcZHrflmc.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-qsWz7r8muII.pt-BR.vtt
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Part 14-Module 02-Lesson 01_Design an AB Test/index.html
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Part 18-Module 04-Lesson 01_Cleaning Data/11. Cleaning For Tidiness -6nMKFhpVCRU.pt-BR.vtt
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Part 21-Module 01-Lesson 01_Why Python Programming/index.html
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/03. Two-Dimensional NumPy Arrays-UFcCmB7Xvvs.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/03. Two-Dimensional NumPy Arrays-UFcCmB7Xvvs.pt-BR.vtt
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Part 11-Module 01-Lesson 16_Tying It All Together/02. Summary-avqZaTECZTQ.ar.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/09. Inspecting Variables and Data-eA8i6-n-Vc4.zh-CN.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/05. Introduction to D3-mP1P0ybdZqI.en-US.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/01. Welcome to the DA Nanodegree Program-FKcIJkTA3GI.pt-BR.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -exMGBx6Rs_E.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/03. Good Data Visualization-ePekYbKs60U.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-hfmvk8DzTGA.ar.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/05. Introduction to D3-mP1P0ybdZqI.en.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/16. Lasso Regression-qU1_cj4LfLY.ar.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/16. Debugging and Inspecting Chart Objects-XYMtkn0DyIM.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/29. From Bars to Circles to Lines-MA-n0Hi3Wyg.en.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/03. Resume Structure-POM0MqLTj98.pt-BR.vtt
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/03. Resume Structure-POM0MqLTj98.pt-BR.vtt
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/03. Resume Structure-POM0MqLTj98.pt-BR.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/02. Arithmetic Operators-M8TIOK2P2yw.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/22. NEW D3 Scale Syntax-nqi4oT2aeAw.zh-CN.vtt
3.8 kB
Part 05-Module 02-Lesson 05_Deeper into SQL/14. Writing Code with DB API-Zd0PAgb6vY4.pt-BR.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/15. Filtering and Segmenting Example-WgM3cBEtkqg.zh-CN.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/27. Empirical Variability Bootstrapping-YW-uud_btQ8.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/19. Using Beautiful Soup-_rDjie-TaS8.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size-4-MF0UZac8o.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/19. Plotting for DataFrames-CDVgPA0Mv2o.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/10. Inspect GeoJSON-ThA4r4nzyj4.ar.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/19. Plotting for DataFrames-CDVgPA0Mv2o.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-Z4n3jR-FZP8.ar.vtt
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Part 16-Module 02-Lesson 04_Programming Workflow for Data Analysis/index.html
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-MlE3BuOvWnU.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-28iU6GrDVfU.zh-CN.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/10. Techniques to Gather Additional Data-6mTsvU0ML94.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/10. NumPy Index Arrays-MlE3BuOvWnU.en.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/20. Regex Operator-MbJfmI7kzQI.en.vtt
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Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/14. What is plot.ly-ZRiAWz-sVlM.ar.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/11. Gotchas Simpson’s Paradox-Tx_jtCfrbt0.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/16. Data Types-ZqRIS9etBqY.zh-CN.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/04. Data Types - Data Visualization and D3.js-ZqRIS9etBqY.zh-CN.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/13. Interview with Art - Part 3-M6PKr3S1rPg.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-NjuenhkC-44.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/23. Nonparametric Answers-Z0QcZHrflmc.pt-BR.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/03. Resume Structure-POM0MqLTj98.es-MX.vtt
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/03. Resume Structure-POM0MqLTj98.es-MX.vtt
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/03. Resume Structure-POM0MqLTj98.es-MX.vtt
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Part 11-Module 01-Lesson 09_Clustering/11. K-Means Clustering Visualization 3-WfwX3B4d8_I.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/24. Annotations World Cup Attendance Chart-Aq39o9xrW5A.pt-BR.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/08. Standard Deviation Calculation-H5zA1A-XPoY.en.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/16. Type Type Conversion-yN6Fam_vZrU.pt-BR.vtt
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Part 21-Module 01-Lesson 05_Scripting/11. Errors And Exceptions-DmthSiy2d0U.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure-CfDLpojt4AY.ar.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/17. More Work Than We Thought-vgJ0ZlxzSiw.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/22. How Page Views Affect Sensitivity-WFVj8QI_uto.zh-CN.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/13. Metric Definition Example-1EoJTK_S0mk.pt-BR.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/25. DATE Functions I-E7Z6GMFVmIY.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/17. Coding It Up-BTFOf2qXy5U.ar.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/20. Plotting With Pandas-kR7KZFqciFE.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps-zSSNWZuVG8Y.ar.vtt
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Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-NvgWKf-iBsw.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/27. Empirical Variability Bootstrapping-YW-uud_btQ8.en.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/03. How This Lesson Is Structured-xfRtO4aFpv0.ar.vtt
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Part 05-Module 01-Lesson 02_Problem Set Data Extraction Fundamentals/index.html
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-KYa8_fuZ30w.ar.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/18. Debugging Data Analysis Code -l1pZZKsESAc.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/12. Related Tables-lMwSjDYgCq0.en.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/11. SELECT FROM Statements-urOYuuav4BY.pt-BR.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/22. SELECT FROM Statements-urOYuuav4BY.pt-BR.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-f1fz9cLnetM.ar.vtt
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Part 11-Module 01-Lesson 16_Tying It All Together/index.html
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Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-w6CLWh1dLCU.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.pt-BR.vtt
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Part 06-Module 01-Lesson 04_Problem Set Analyzing Data/index.html
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Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-YbVuN2KOlt4.ja.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/22. Looking at Samples of Households-kQePh6UTB90.zh-CN.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-QoEqPotgMbA.zh-CN.vtt
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Part 21-Module 01-Lesson 03_Control Flow/25. Break and Continue-F6qJAv9ts9Y.zh-CN.vtt
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/06. Appending And NumPy-fdpKvovBMe4.pt-BR.vtt
3.7 kB
Part 11-Module 01-Lesson 03_SVM/10. SVM in SKlearn-R7xQtQzkvTk.ar.vtt
3.7 kB
Part 13-Module 01-Lesson 04_Design Principles/07. Small Multiples-HS_dsOQfwz8.en.vtt
3.7 kB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/10. Welcome to the end of the lesson-nWFJ_eOU27I.pt-BR.vtt
3.7 kB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/04. Meet the Careers Team-cuKecPpZ7PM.en.vtt
3.7 kB
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-spVqFnSvlIU.zh-CN.vtt
3.7 kB
Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-joTa_FeMZ2s.ja.vtt
3.7 kB
Part 19-Module 01-Lesson 02_Design/03. Exploratory vs. Explanatory Analysis-wvgBSMks4p8.en.vtt
3.7 kB
Part 12-Module 01-Lesson 01_Ace Your Interview/index.html
3.7 kB
Part 18-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces) 2-tobH58uO24U.pt-BR.vtt
3.7 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/23. Making Histograms-0J5lNTGbspg.en.vtt
3.7 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/04. Assessing the Quality of Data Pt. 2-8onBHqvvrig.en.vtt
3.7 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-qgwygpD0eN8.pt-BR.vtt
3.7 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/12. Target Population Example-XsyavvSGjLM.en.vtt
3.7 kB
Part 11-Module 01-Lesson 11_Text Learning/11. Stemming with NLTK-gWbkW_cyNs8.pt-BR.vtt
3.7 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/19. String Methods-Bv7CAxVOONs.pt-BR.vtt
3.7 kB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/01. Welcome to the DA Nanodegree Program-FKcIJkTA3GI.en.vtt
3.7 kB
Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-YbVuN2KOlt4.en.vtt
3.7 kB
Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-wPI9WOfpZbM.ja.vtt
3.7 kB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/05. A Faster Algorithm-J7S3CHFBZJA.en-US.vtt
3.7 kB
Part 09-Module 01-Lesson 02_R Basics/04. Install RStudio on Windows-5ZbjUEg4a1g.ja.vtt
3.7 kB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/05. A Faster Algorithm-J7S3CHFBZJA.en.vtt
3.7 kB
Part 12-Module 02-Lesson 06_Graphs/02. What Is a Graph-p-_DFOyEMV8.zh-CN.vtt
3.7 kB
Part 17-Module 01-Lesson 13_Case Study AB tests/02. AB Testing-EcWvhbIjT9o.pt-BR.vtt
3.7 kB
Part 18-Module 02-Lesson 01_Gathering Data/20. Flashforward 2-Sbyn8aT-8G8.pt-BR.vtt
3.7 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/06. Connecting To Data-WmsAtqbwRI0.ar.vtt
3.7 kB
Part 12-Module 02-Lesson 02_List-Based Collections/03. Arrays-OnPP5xDmFv0.zh-CN.vtt
3.7 kB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/05. Writing the Body-aK9Qnv3a6Wg.en.vtt
3.7 kB
Part 12-Module 02-Lesson 02_List-Based Collections/06. Linked Lists in Depth-ZONGA5wmREI.zh-CN.vtt
3.7 kB
Part 13-Module 01-Lesson 05_Dimple.js/01. Dimple Interlude-bo8_lJucTPI.pt-BR.vtt
3.7 kB
Part 17-Module 01-Lesson 13_Case Study AB tests/07. Metric - Click Through Rate-EpfoKAwV_Eg.en.vtt
3.7 kB
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/02. Exploring data with Trina-sLzULEjMY1E.zh-CN.vtt
3.7 kB
Part 05-Module 01-Lesson 05_Data Quality/07. A Blueprint for Cleaning-3S73cNbhuAk.ar.vtt
3.7 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-xsdj1qJwgk4.pt-BR.vtt
3.7 kB
Part 17-Module 01-Lesson 08_Python Probability Practice/02. Simulating Coin Flips-7YtQNZ3iy6o.en.vtt
3.7 kB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/08. 05 Hierarchies-vkHeQcI08yc.zh-CN.vtt
3.7 kB
Part 18-Module 03-Lesson 01_Assessing Data/07. Visual Assessment -GVVibuIg3Ro.pt-BR.vtt
3.7 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/33. Highlight Countries-bq_gVndUj1U.zh-CN.vtt
3.7 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/20. Calculating the p-value-_W3Jg7jQ8jI.en.vtt
3.7 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/20. Broken Requests-QFjKVSmxODY.ar.vtt
3.7 kB
Part 13-Module 01-Lesson 04_Design Principles/51. D3 Functions-4OkB_Ybo0i0.pt-BR.vtt
3.7 kB
Part 13-Module 01-Lesson 07_Narrative Structures/62. Adding Circles to the Legend-FlbCPYGCKqk.pt-BR.vtt
3.7 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/01. Intro-UJyJm79RS88.en-US.vtt
3.7 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/20. Calculating the p-value-_W3Jg7jQ8jI.pt-BR.vtt
3.7 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/01. Intro-UJyJm79RS88.en.vtt
3.7 kB
Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results-ZFn9xVQ0hD4.ar.vtt
3.7 kB
Part 13-Module 01-Lesson 07_Narrative Structures/36. Circles with Bound __data__-JeJ_glcExUs.ar.vtt
3.7 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-EwV5Vs2m33w.ar.vtt
3.7 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/17. More Work Than We Thought-vgJ0ZlxzSiw.pt-BR.vtt
3.7 kB
Part 11-Module 01-Lesson 12_Feature Selection/15. Regularization-l9V5tlIWTvs.en.vtt
3.7 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/10. Estimating Click-Through-Probability-Hkbc_vcb7D8.ar.vtt
3.7 kB
Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-YaZu4waSryo.ja.vtt
3.7 kB
Part 11-Module 01-Lesson 12_Feature Selection/15. Regularization-l9V5tlIWTvs.pt-BR.vtt
3.7 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/09. Metric Choice-BeIy4A6YKrY.zh-CN.vtt
3.7 kB
Part 21-Module 01-Lesson 03_Control Flow/28. Zip and Enumerate-bSJPzVArE7M.ar.vtt
3.7 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/05. NumPy and Pandas Data Types-seEFuJ-qvlg.zh-CN.vtt
3.7 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/05. NumPy and Pandas Data Types-seEFuJ-qvlg.zh-CN.vtt
3.7 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/28. Multi Update-tuXc0Ycy_yM.en.vtt
3.7 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots-GmR3uEM189M.ar.vtt
3.7 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/03. Good Data Visualization-ePekYbKs60U.en-US.vtt
3.7 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-Hs3__UsSyL8.ar.vtt
3.7 kB
Part 06-Module 01-Lesson 02_Problem Set Working with MongoDB/index.html
3.7 kB
Part 18-Module 02-Lesson 01_Gathering Data/09. Trees-OVeJU18ADmw.ar.vtt
3.7 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/12. DataFrame apply()-KSZ2XLYk4hk.pt-BR.vtt
3.7 kB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/05. A Faster Algorithm-J7S3CHFBZJA.pt-BR.vtt
3.7 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-gfuknvEP2ro.pt-BR.vtt
3.7 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/12. DataFrame apply()-KSZ2XLYk4hk.pt-BR.vtt
3.7 kB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/09. Reviewing our Street Name Audit-eIvm5rEMZGY.en.vtt
3.7 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-GXT_vXBA0vQ.pt-BR.vtt
3.7 kB
Part 13-Module 01-Lesson 07_Narrative Structures/27. Defining a Join-Xo-OJXzS0tQ.ar.vtt
3.7 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/10. Details of the Data Science Process-8TeiMKUmoYQ.pt-BR.vtt
3.7 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/03. Good Data Visualization-ePekYbKs60U.en.vtt
3.7 kB
Part 13-Module 01-Lesson 07_Narrative Structures/43. D3 Parsing Dates and Times-DrOoJJWRAno.pt-BR.vtt
3.6 kB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-c-v-Xa_R4SA.ja.vtt
3.6 kB
Part 18-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment -BNRJdhA8_s8.pt-BR.vtt
3.6 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/10. Inter- vs. Intra-User Experiments-EGE8ddtWIeo.zh-CN.vtt
3.6 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/04. 29 Number Summary-gzUN5zKLHjQ.en.vtt
3.6 kB
Part 13-Module 01-Lesson 05_Dimple.js/16. Debugging and Inspecting Chart Objects-XYMtkn0DyIM.en.vtt
3.6 kB
Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-fRNDqy-le8U.pt-BR.vtt
3.6 kB
Part 18-Module 03-Lesson 01_Assessing Data/07. Visual Assessment -GVVibuIg3Ro.en.vtt
3.6 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/08. Overview of Business Example-tlSe7H9BDy8.en.vtt
3.6 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/14. Population vs. Cohort Example-MXukXfzL59E.zh-CN.vtt
3.6 kB
Part 11-Module 01-Lesson 14_Validation/03. TrainTest Split in sklearn-lSwvUmZCvco.zh-CN.vtt
3.6 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. Assess Intro -vj3CYBlWj3k.ar.vtt
3.6 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/03. Two-Dimensional NumPy Arrays-UFcCmB7Xvvs.en.vtt
3.6 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/02. Intro to XML-eIVifBVJQIw.pt-BR.vtt
3.6 kB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/02. Elevator Pitch-S-nAHPrkQrQ.es-MX.vtt
3.6 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/03. Two-Dimensional NumPy Arrays-UFcCmB7Xvvs.en.vtt
3.6 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/40. Calculated Fields-tR-K9Mvd4B0.ar.vtt
3.6 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/28. Multi Update-tuXc0Ycy_yM.pt-BR.vtt
3.6 kB
Part 05-Module 02-Lesson 01_Data and Tables/13. Uniqueness and Keys-TIayTr4y9RA.en.vtt
3.6 kB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/10. Welcome to the end of the lesson-nWFJ_eOU27I.en.vtt
3.6 kB
Part 13-Module 01-Lesson 07_Narrative Structures/53. Inspecting Accessor Functions-bRkkMdkkFQw.pt-BR.vtt
3.6 kB
Part 06-Module 01-Lesson 03_Analyzing Data/02. Twitter Data Set-xiqleK_px_Q.en-US.vtt
3.6 kB
Part 11-Module 01-Lesson 04_Decision Trees/34. DT Strengths and Weaknesses-KGnhg76iRfI.ar.vtt
3.6 kB
Part 06-Module 01-Lesson 03_Analyzing Data/02. Twitter Data Set-xiqleK_px_Q.en.vtt
3.6 kB
Part 14-Module 01-Lesson 05_Analyzing Results/10. Single Metric Gotchas-WrfWFLiFeMU.zh-CN.vtt
3.6 kB
Part 16-Module 03-Lesson 02_SQL Joins/18. JOINs and Filtering-aI1kbDDNs4w.en.vtt
3.6 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-E3NhvAC3Ghw.pt-BR.vtt
3.6 kB
Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-jkJ4dbbpVCQ.ja.vtt
3.6 kB
Part 05-Module 01-Lesson 05_Data Quality/15. Auditing Completeness-PMbcv9AYQT4.zh-CN.vtt
3.6 kB
Part 12-Module 02-Lesson 03_Searching and Sorting/07. Bubble Sort-h_osLG3GmjE.pt-BR.vtt
3.6 kB
Part 09-Module 01-Lesson 03_Explore One Variable/21. Lada's Money Bag Meme-Isa_FGQrvgs.zh-CN.vtt
3.6 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-xsdj1qJwgk4.en.vtt
3.6 kB
Part 13-Module 01-Lesson 04_Design Principles/36. Less is More-urgyRvfWPtU.ar.vtt
3.6 kB
Part 06-Module 01-Lesson 03_Analyzing Data/02. Twitter Data Set-xiqleK_px_Q.pt-BR.vtt
3.6 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/13. Worksheets-2xRKvQTRtlk.zh-CN.vtt
3.6 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.en-US.vtt
3.6 kB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.en-US.vtt
3.6 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.en.vtt
3.6 kB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.en.vtt
3.6 kB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/02. Elevator Pitch-S-nAHPrkQrQ.en.vtt
3.6 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/06. Accessing Elements of a DataFrame-4RmQYWI8lY4.en.vtt
3.6 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/06. Accessing Elements of a DataFrame-4RmQYWI8lY4.en.vtt
3.6 kB
Part 12-Module 02-Lesson 03_Searching and Sorting/07. Bubble Sort-h_osLG3GmjE.zh-CN.vtt
3.6 kB
Part 21-Module 01-Lesson 03_Control Flow/31. List Comprehensions-6qxo-NV9v_s.pt-BR.vtt
3.6 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/07. Packages Overview-sCQoQsmI3F0.ar.vtt
3.6 kB
Part 04-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.zh-CN.vtt
3.6 kB
Part 16-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.zh-CN.vtt
3.6 kB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/06. Dynamic Programming-VQeFcG9pjJU.en-US.vtt
3.6 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-Mta8Hv36k7Q.ar.vtt
3.6 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-Mta8Hv36k7Q.ar.vtt
3.6 kB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/06. Dynamic Programming-VQeFcG9pjJU.en.vtt
3.6 kB
Part 14-Module 01-Lesson 05_Analyzing Results/03. Choosing Invariants-E1ePfjcVH3I.zh-CN.vtt
3.6 kB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.th.vtt
3.6 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/29. Collecting Participating Countries-ha6kGtT9XMQ.pt-BR.vtt
3.6 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/12. Gathering Data-JsVg95-amjI.pt-BR.vtt
3.6 kB
Part 16-Module 03-Lesson 03_SQL Aggregations/01. Introduction to Aggregations-5vRf_Ntoxfw.ar.vtt
3.6 kB
Part 05-Module 01-Lesson 05_Data Quality/05. Measuring Data Quality-dj46LqDBFYM.ar.vtt
3.6 kB
Part 11-Module 01-Lesson 13_PCA/23. PCA for Feature Transformation-8kUPRUEMCA8.zh-CN.vtt
3.6 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/22. Random Observed Values-KFIt2OC3wCI.ar.vtt
3.6 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/25. Aggregations-ADx1x2ljFB4.ar.vtt
3.6 kB
Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-CPDMSJEH16s.ja.vtt
3.6 kB
Part 11-Module 01-Lesson 09_Clustering/10. K-Means Clustering Visualization 2-fQXXa-CAoS0.en.vtt
3.6 kB
Part 13-Module 01-Lesson 07_Narrative Structures/28. Joins in D3-rDjOINfKftY.zh-CN.vtt
3.6 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/27. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.pt-BR.vtt
3.6 kB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.pt-BR.vtt
3.6 kB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/07. Efficiency-I-RASDPbDrI.en-US.vtt
3.6 kB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/03. Dijkstra's Algorithm-SoPMK03cOgk.en-US.vtt
3.6 kB
Part 12-Module 02-Lesson 08_Technical Interview - Python/09. Debugging-Bz1tlvkql9Q.pt-BR.vtt
3.6 kB
Part 13-Module 01-Lesson 05_Dimple.js/29. From Bars to Circles to Lines-MA-n0Hi3Wyg.zh-CN.vtt
3.6 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/20. Practical, or Substantive, Significance-Q576t5aaZ34.zh-CN.vtt
3.6 kB
Part 09-Module 01-Lesson 02_R Basics/04. Install RStudio on Windows-5ZbjUEg4a1g.pt-BR.vtt
3.6 kB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/07. Efficiency-I-RASDPbDrI.en.vtt
3.6 kB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/03. Dijkstra's Algorithm-SoPMK03cOgk.en.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/32. Binding Data-yW9LEMFOzgY.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/06. Accessing Elements of a DataFrame-4RmQYWI8lY4.pt-BR.vtt
3.6 kB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/03. Dijkstra's Algorithm-SoPMK03cOgk.pt-BR.vtt
3.6 kB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Window Functions-gp0RPgkDHsQ.ar.vtt
3.6 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/06. Accessing Elements of a DataFrame-4RmQYWI8lY4.pt-BR.vtt
3.6 kB
Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-YaZu4waSryo.pt-BR.vtt
3.6 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/11. Introducing the Working Example-ax7aaLNZkPA.ar.vtt
3.6 kB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/14. What is the Question-xQJyObqxg3E.zh-CN.vtt
3.6 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/17. Sizing Example-f69Hs7m1axc.zh-CN.vtt
3.6 kB
Part 13-Module 01-Lesson 07_Narrative Structures/24. Annotations World Cup Attendance Chart-Aq39o9xrW5A.en-US.vtt
3.6 kB
Part 21-Module 01-Lesson 05_Scripting/26. Third Party Libraries And Package Managers-epOze9gC6T4.en.vtt
3.6 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/13. Metric Definition Example-1EoJTK_S0mk.en.vtt
3.6 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/07. History of AB Testing-NNiKGao0xnk.zh-CN.vtt
3.6 kB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.ar.vtt
3.6 kB
Part 16-Module 03-Lesson 03_SQL Aggregations/25. DATE Functions I-E7Z6GMFVmIY.en.vtt
3.6 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/20. Outliers-HKIsvkZUZfo.ar.vtt
3.6 kB
Part 13-Module 01-Lesson 07_Narrative Structures/24. Annotations World Cup Attendance Chart-Aq39o9xrW5A.en.vtt
3.6 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.pt-BR.vtt
3.6 kB
Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.th.vtt
3.6 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.pt-BR.vtt
3.6 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/29. Removing Documents-oFWNOvxuIRQ.pt-BR.vtt
3.6 kB
Part 03-Module 01-Lesson 07_Google Spreadsheet Tutorial/index.html
3.6 kB
Part 06-Module 01-Lesson 03_Analyzing Data/08. Match Operator-FZ8KVv1VOK4.ar.vtt
3.6 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/06. Choosing Metrics-mOH45PzylKk.ar.vtt
3.6 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/01. Intro-UJyJm79RS88.zh-CN.vtt
3.6 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/13. Getting Data into MongoDB-hi6g1NE3sPk.pt-BR.vtt
3.6 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/20. Hierarchies-wl_AM-spH68.zh-CN.vtt
3.6 kB
Part 12-Module 01-Lesson 04_Land a Job Offer/index.html
3.6 kB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Aggregates in Window Functions-Dxew5w3VF7k.ar.vtt
3.6 kB
Part 19-Module 01-Lesson 02_Design/15. Shape, Size, and other Tools-fzEliHW3ZLM.en.vtt
3.6 kB
Part 05-Module 02-Lesson 05_Deeper into SQL/14. Writing Code with DB API-Zd0PAgb6vY4.en.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment -BNRJdhA8_s8.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/14. Helpful Symbols-w4_8YCp-9fI.pt-BR.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys-fnbLMcd0FGQ.pt-BR.vtt
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/02. Elevator Pitch-S-nAHPrkQrQ.pt-BR.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/20. Flashforward 2-Sbyn8aT-8G8.en.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/09. HTML Structure-UjCbXQ8Coic.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/51. D3 Functions-4OkB_Ybo0i0.en.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size-4-MF0UZac8o.en.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.it.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces) 2-tobH58uO24U.en.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/03. Resume Structure-POM0MqLTj98.en.vtt
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/03. Resume Structure-POM0MqLTj98.en.vtt
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/03. Resume Structure-POM0MqLTj98.en.vtt
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Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-joTa_FeMZ2s.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/62. Adding Circles to the Legend-FlbCPYGCKqk.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.ar.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-UkGwgerJU44.ar.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/32. Binding Data-yW9LEMFOzgY.en.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/04. Assessing the Quality of Data Pt. 2-8onBHqvvrig.pt-BR.vtt
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Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-vLlj5nNj8x4.ja.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-8zWQmAVPthY.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/20. Extracting Score Data from sklearn-NhD4oUuhvO8.ar.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/13. Text File Structure-O4qEWpXZLQg.pt-BR.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/13. Pandas Series-8zWQmAVPthY.zh-CN.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/19. Exists-j5l5UvE3Odw.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/38. Communicating Your Message-wZt6fXEUqQM.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/29. Collecting Participating Countries-ha6kGtT9XMQ.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-gfuknvEP2ro.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.it.vtt
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Part 11-Module 01-Lesson 07_Regressions/19. Extracting Information from sklearn-zDIRQE_oxfk.zh-CN.vtt
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/06. Dynamic Programming-VQeFcG9pjJU.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/37. setInterval and clearInterval-r1sgfqg85us.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/06. Choosing Metrics-eAukkpVFl5c.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-SwbreslrpqQ.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.es-ES.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/02. Case Study US Unemployment-R6Nk8NsEzUA.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/03. The Benefits of Interactivity-fIIyFYQyGLk.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/17. More Work Than We Thought-vgJ0ZlxzSiw.zh-CN.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/08. Efficiency of Bubble Sort-KddkHygi7is.en-US.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/02. Defining Data Visualization-TMH43G11OnQ.pt-BR.vtt
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Part 04-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.en.vtt
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Part 16-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/04. Statistical Significance-kpdwHL54eys.pt-BR.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/08. Efficiency of Bubble Sort-KddkHygi7is.en.vtt
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/02. Cleaning with String Functions-y1fduSu7Ovc.pt-BR.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/03. Normalized Design Part Two-l6SDnhM7B_k.zh-CN.vtt
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Part 21-Module 01-Lesson 01_Why Python Programming/04. L1 02 Course Overview V4-vFxXSIV5cHM.ar.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/15. Using mongoimport-JVYH9B6Obpg.ar.vtt
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Part 21-Module 01-Lesson 03_Control Flow/20. L3 08 While Loops V3-7Sf5tcPlKQw.pt-BR.vtt
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Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-FDSmlIBy7ko.zh-CN.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/22. Simulation Applet-yu4mdXybrts.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/19. Pre-attentive Attributes-6UvLbIX0NQ4.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/14. Loading Data with Nested Functions-ME6F4Nyjv8o.pt-BR.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/15. What About More Than Two Variables -ufKcdUbLj9c.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-E3NhvAC3Ghw.en.vtt
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Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-krV6r7HxmZU.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/14. Helpful Symbols-w4_8YCp-9fI.es.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/06. Accessing Elements of a DataFrame-hZp9cVuiPo0.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/06. Accessing Elements of a DataFrame-hZp9cVuiPo0.pt-BR.vtt
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Part 21-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.ar.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/02. Intro to XML-eIVifBVJQIw.en-US.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/02. Arithmetic Operators-M8TIOK2P2yw.en.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/02. Intro to XML-eIVifBVJQIw.en.vtt
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Part 21-Module 01-Lesson 04_Functions/08. Documentation-_Vl9NJkA6JQ.ar.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-E3NhvAC3Ghw.ja.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/01. t-Distribution-N6wKbV1DVos.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.es-ES.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/08. Report Results-xNbzHOnSx5Q.zh-CN.vtt
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Part 04-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.ar.vtt
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Part 12-Module 02-Lesson 01_Introduction and Efficiency/08. Notation Intro-xHwIU4j3gBc.zh-CN.vtt
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Part 16-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data-8FD_iOP24UA.pt-BR.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/16. Assess Programmatic-6JubHCD7dh4.pt-BR.vtt
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/02. Elevator Pitch-S-nAHPrkQrQ.zh-CN.vtt
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Running Totals And Count-rNJwmnzUTxg.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/06. Interval Estimate for Population Mean-ECRw3cSiy6o.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data-zQj_waidR5w.ar.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/02. Defining Data Visualization-TMH43G11OnQ.en-US.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/03. Facebook Experiment-VqLX0wnrldc.ar.vtt
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/12. Related Tables-lMwSjDYgCq0.zh-CN.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/04. Interview with Art - Part 1-ClLYamtaO-Q.zh-CN.vtt
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Part 12-Module 02-Lesson 06_Graphs/13. Eulerian Path-zS34kHSo7fs.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/02. Defining Data Visualization-TMH43G11OnQ.en.vtt
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Part 21-Module 01-Lesson 05_Scripting/21. The Standard Library-Fw3vf0tDrJM.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-V7zAB9dUaFY.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/16. Debugging and Inspecting Chart Objects-XYMtkn0DyIM.zh-CN.vtt
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Part 17-Module 01-Lesson 14_Regression/13. Fitting A Regression Line-xQob80zrT3s.pt-BR.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/13. Pandas Series-V7zAB9dUaFY.pt-BR.vtt
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Part 21-Module 01-Lesson 05_Scripting/13. Handling Errors Try Except Finally-S6hwBZG0KwM.pt-BR.vtt
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Part 11-Module 01-Lesson 09_Clustering/10. K-Means Clustering Visualization 2-fQXXa-CAoS0.pt-BR.vtt
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/06. Appending And NumPy-fdpKvovBMe4.en.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/31. L2 02 Dictionaries And Identiy Operators V3-QR8HTxCTWi0.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/31. Data Join with a Key Function-ue_TULswM1Y.pt-BR.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/11. Gotchas Simpson’s Paradox-Tx_jtCfrbt0.en.vtt
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/08. Exact and Approximate Algorithms-3A8YqOYlAwQ.zh-CN.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/06. Words of Wisdom from Zipfian Academy-ani9_ZalK-8.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.th.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/12. Creating and Drawing the Chart-ZyhYNaRqqL0.ar.vtt
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Part 11-Module 01-Lesson 11_Text Learning/11. Stemming with NLTK-gWbkW_cyNs8.zh-CN.vtt
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Part 12-Module 02-Lesson 06_Graphs/13. Eulerian Path-zS34kHSo7fs.en-US.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/17. Different Types of Narrative Structures-vTlpDo33ezg.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.en.vtt
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Part 12-Module 02-Lesson 06_Graphs/13. Eulerian Path-zS34kHSo7fs.en.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/20. Flashforward 2-Sbyn8aT-8G8.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.pt-BR.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1 Solution -I1enB5CA85Q.ar.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/03. Get to Know the PDF-52HAbu6_u9I.pt-BR.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/19. String Methods-Bv7CAxVOONs.en.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/08. Calculating Correlation-yLql7kR_6GE.pt-BR.vtt
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Part 09-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.ar.vtt
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Part 09-Module 01-Lesson 02_R Basics/04. Install RStudio on Windows-5ZbjUEg4a1g.en.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/16. Sizing Overview-sKRWt_iS7zo.pt-BR.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/07. What is the Standard Deviation Measuring-IbwUJ3ORZ5s.ar.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/08. Calculating Correlation-yLql7kR_6GE.pt-BR.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/20. Absolute or Relative Difference-TNcT_v2g3OQ.en.vtt
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Part 11-Module 01-Lesson 13_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-jkJ4dbbpVCQ.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/08. Declaring Relationships-1FjqstT1faI.pt-BR.vtt
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Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-GuBics_6HOk.ar.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/06. CSV Format-ra93hy88cok.pt-BR.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/43. Table Calculations-VJfCNO0J9jY.ar.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-V7zAB9dUaFY.en.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/13. Pandas Series-V7zAB9dUaFY.en.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/10. Boolean Comparison and Logical Operators-iNNsUJIDtVU.pt-BR.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/02. Data Modeling in MongoDB-6sDkIE_nAGI.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.es.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-GXT_vXBA0vQ.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/02. Problems Solved by Data Analysts-jZEbCVZzwUk.pt-BR.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/02. What Is A POI-wDQhif-MWuY.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/36. Naive Bayes Strengths and Weaknesses-nfbKTrufPOs.ja.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/14. Balancing Error with Number of Features-IwiIFMcDwoA.zh-CN.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/15. Joining Tables-lXoiI0gx3MU.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/43. D3 Parsing Dates and Times-DrOoJJWRAno.en.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-wPI9WOfpZbM.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-S-pjRUJAGTs.ar.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-iJEBxsKDDoE.ja.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/16. Sizing Overview-sKRWt_iS7zo.en.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/13. GROUP BY-9vb67TF4WV0.pt-BR.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/19. What Is A P-value Anyway-eU6pUZjqviA.zh-CN.vtt
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/05. A Faster Algorithm-J7S3CHFBZJA.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/41. Parsing Data Before the Draw Function-WALbqgiDHNI.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.th.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-YaZu4waSryo.en.vtt
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Part 19-Module 01-Lesson 02_Design/05. What Makes a Bad Visual-zbvB_9f7bFs.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/19. Viewer-driven Examples-ft07qc8rTwM.pt-BR.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/12. Gathering Data-JsVg95-amjI.en.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/11. SELECT FROM Statements-urOYuuav4BY.en.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/22. SELECT FROM Statements-urOYuuav4BY.en.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/05. Investigation Process-5o2x4UsumLY.ar.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/07. Univariate Plots-kgmYLreYB0A.ar.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye-sJgPnuiHrs8.ar.vtt
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Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-tfYAGBIR_Ws.ar.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-fo4MJMkwhYU.en.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/11. Other Techniques Example-sOGuF3it6Ek.zh-CN.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values-l3ergsxocok.pt-BR.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/20. Regex Operator-MbJfmI7kzQI.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values-l3ergsxocok.pt-BR.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/02. Data Modeling in MongoDB-6sDkIE_nAGI.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/19. Checking the Nest Return-hCXhsYVLqig.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-joTa_FeMZ2s.en.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/13. Getting Data into MongoDB-hi6g1NE3sPk.zh-CN.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/29. Removing Documents-oFWNOvxuIRQ.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/13. Uniqueness and Keys-TIayTr4y9RA.zh-CN.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.ar.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/01. Dimple Interlude-bo8_lJucTPI.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-fRNDqy-le8U.en.vtt
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Part 19-Module 01-Lesson 02_Design/05. What Makes a Bad Visual-zbvB_9f7bFs.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/20. Clean Define-qHB4jsqcfi4.en.vtt
3.4 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/15. Hypotheses-DepOzUJw_bQ.pt-BR.vtt
3.4 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/17. Range Queries-6r5Xc-_lhEI.zh-CN.vtt
3.4 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/15. Hypotheses-DepOzUJw_bQ.en.vtt
3.4 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/26. Updates-mpMHJQalRck.pt-BR.vtt
3.4 kB
Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-x-8-2zy8gmI.en.vtt
3.4 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-74mudn321tA.es.vtt
3.4 kB
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.en.vtt
3.4 kB
Part 17-Module 01-Lesson 08_Python Probability Practice/04. Simulating Many Coin Flips-AqpWQIj2V5Y.pt-BR.vtt
3.4 kB
Part 17-Module 01-Lesson 11_Confidence Intervals/08. Statistical vs. Practical Differences-RKHD1wzxxPA.pt-BR.vtt
3.4 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/08. Map Distortions-xL5xVEuLuNE.ar.vtt
3.4 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1-mUfrDUEEa_k.en.vtt
3.4 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-fo4MJMkwhYU.pt-BR.vtt
3.4 kB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.ar.vtt
3.4 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/17. Simulating From the Null-sL2yJtHZd8Y.en.vtt
3.4 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ivBGyL3SzO0.ar.vtt
3.4 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/48. Matt's Tips for Making Maps-HCYCT2TXhAM.pt-BR.vtt
3.4 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/08. Unit of Analysis vs. Unit of Diversion-rzim0wu_0kM.en.vtt
3.4 kB
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-HEnJRwJ23us.ja.vtt
3.4 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1-mUfrDUEEa_k.zh-CN.vtt
3.4 kB
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-vLlj5nNj8x4.en.vtt
3.4 kB
Part 05-Module 01-Lesson 05_Data Quality/09. Auditing Validity-B9vjn8IYaSg.ar.vtt
3.4 kB
Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.ar.vtt
3.4 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/48. Matt's Tips for Making Maps-HCYCT2TXhAM.en.vtt
3.4 kB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/01. Welcome to the DA Nanodegree Program-FKcIJkTA3GI.zh-CN.vtt
3.4 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/14. Loading Data with Nested Functions-ME6F4Nyjv8o.en.vtt
3.4 kB
Part 05-Module 01-Lesson 05_Data Quality/19. More About Correcting Data-vWBMgSQvsVk.pt-BR.vtt
3.4 kB
Part 05-Module 02-Lesson 05_Deeper into SQL/14. Writing Code with DB API-Zd0PAgb6vY4.zh-CN.vtt
3.4 kB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/09. Reviewing our Street Name Audit-eIvm5rEMZGY.pt-BR.vtt
3.4 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/12. DataFrame apply()-KSZ2XLYk4hk.en.vtt
3.4 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/12. DataFrame apply()-KSZ2XLYk4hk.en.vtt
3.4 kB
Part 05-Module 01-Lesson 05_Data Quality/17. Consistency-_5AnMdslWg4.pt-BR.vtt
3.4 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-74mudn321tA.en-US.vtt
3.4 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-74mudn321tA.en.vtt
3.4 kB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-IwcoGtFuYSo.ar.vtt
3.4 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/34. From Source Code to Graphic-PIqgFTee-lk.ar.vtt
3.4 kB
Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-CPDMSJEH16s.zh-CN.vtt
3.4 kB
Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-OurfO1ZR2GU.pt-BR.vtt
3.4 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-9L9bhMCHQ-M.en.vtt
3.4 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-qgwygpD0eN8.en.vtt
3.4 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1-J4X9r0EGH3k.ar.vtt
3.4 kB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/03. Get to Know the PDF-52HAbu6_u9I.en.vtt
3.4 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/05. Intro to CSVs-UFiJYYPL95g.pt-BR.vtt
3.4 kB
Part 11-Module 01-Lesson 07_Regressions/27. Problem with Minimizing Absolute Errors-U46D7oEijlI.zh-CN.vtt
3.4 kB
Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-jkJ4dbbpVCQ.pt-BR.vtt
3.4 kB
Part 12-Module 02-Lesson 06_Graphs/10. DFS-BC8jEidd2EQ.en-US.vtt
3.4 kB
Part 21-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.pt-BR.vtt
3.4 kB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.zh-CN.vtt
3.4 kB
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.ja.vtt
3.4 kB
Part 21-Module 01-Lesson 05_Scripting/27. Experimenting With An Interpreter-hspPtnQwMPg.zh-CN.vtt
3.4 kB
Part 12-Module 02-Lesson 06_Graphs/10. DFS-BC8jEidd2EQ.en.vtt
3.4 kB
Part 13-Module 01-Lesson 07_Narrative Structures/53. Inspecting Accessor Functions-bRkkMdkkFQw.en.vtt
3.4 kB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/17. Type And Quality Plot - Part 2-Ui1rF6McOBA.ar.vtt
3.4 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/28. Multi Update-tuXc0Ycy_yM.zh-CN.vtt
3.4 kB
Part 12-Module 02-Lesson 04_Maps and Hashing/05. Hashing-kCPFfHx_LgQ.en-US.vtt
3.4 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.ar.vtt
3.4 kB
Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files-w-ZG6DMkVi4.ar.vtt
3.4 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/28. Improving Plots and Sharing Findings-anglRHbmsfw.ar.vtt
3.4 kB
Part 12-Module 02-Lesson 04_Maps and Hashing/05. Hashing-kCPFfHx_LgQ.en.vtt
3.4 kB
Part 13-Module 01-Lesson 07_Narrative Structures/04. The New Journalism-ub1_Gwc6wN8.zh-CN.vtt
3.4 kB
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.en.vtt
3.4 kB
Part 18-Module 02-Lesson 01_Gathering Data/13. Text File Structure-O4qEWpXZLQg.en.vtt
3.4 kB
Part 17-Module 01-Lesson 11_Confidence Intervals/11. Traditional vs. Bootstrapping Confidence Intervals-eZ8lyiumXDY.en.vtt
3.4 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/09. Gather Open Jupyter Notebook-IaExjsrVMgQ.ar.vtt
3.4 kB
Part 21-Module 01-Lesson 05_Scripting/08. Scripting With Raw Input-Fs9uLV2qfgI.pt-BR.vtt
3.4 kB
Part 19-Module 01-Lesson 02_Design/16. General Design Tips-Zq-wMwOfQqY.ar.vtt
3.4 kB
Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-VYwgHHqaUII.ar.vtt
3.4 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/10. Details of the Data Science Process-8TeiMKUmoYQ.en.vtt
3.4 kB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.ja.vtt
3.4 kB
Part 12-Module 02-Lesson 04_Maps and Hashing/05. Hashing-kCPFfHx_LgQ.pt-BR.vtt
3.4 kB
Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-TjY0Q66Yh-s.pt-BR.vtt
3.4 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/10. -v5CqqhgvG-U.en-US.vtt
3.4 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/24. MM CLT-DqC-pgcEam4.pt-BR.vtt
3.4 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/26. Updates-mpMHJQalRck.en.vtt
3.4 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/10. -v5CqqhgvG-U.en.vtt
3.4 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/23. McDonald's-29Vf6PytVbA.pt-BR.vtt
3.4 kB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/23. McDonald's-29Vf6PytVbA.pt-BR.vtt
3.4 kB
Part 11-Module 01-Lesson 14_Validation/09. K-Fold CV in sklearn-QSYMwFbE7PA.zh-CN.vtt
3.3 kB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-c-v-Xa_R4SA.zh-CN.vtt
3.3 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-Q2M8xyY47fc.pt-BR.vtt
3.3 kB
Part 11-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary-gBwGPI0srBE.pt-BR.vtt
3.3 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/17. Simulating From the Null-sL2yJtHZd8Y.pt-BR.vtt
3.3 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/13. Thematic Maps-Jw2q-B2kM9k.ar.vtt
3.3 kB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/05. Writing the Body-aK9Qnv3a6Wg.pt-BR.vtt
3.3 kB
Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-eAKVYAR_VlY.ar.vtt
3.3 kB
Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces--VxKwVvrNY0.ar.vtt
3.3 kB
Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces--VxKwVvrNY0.ar.vtt
3.3 kB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/03. Resume Structure-POM0MqLTj98.zh-CN.vtt
3.3 kB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/03. Resume Structure-POM0MqLTj98.zh-CN.vtt
3.3 kB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/03. Resume Structure-POM0MqLTj98.zh-CN.vtt
3.3 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/23. McDonald's-29Vf6PytVbA.en.vtt
3.3 kB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/23. McDonald's-29Vf6PytVbA.en.vtt
3.3 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/12. Iterating on Visualizations-muh0thR2DKo.ar.vtt
3.3 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -CSW2i2jIqyA.pt-BR.vtt
3.3 kB
Part 17-Module 01-Lesson 05_Binomial Distribution/16. Binomial Distribution Conclusion-9gjCYs8f_PU.pt-BR.vtt
3.3 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-9L9bhMCHQ-M.pt-BR.vtt
3.3 kB
Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-paj5z9U1OBk.pt-BR.vtt
3.3 kB
Part 16-Module 03-Lesson 02_SQL Joins/02. Why Use Separate Tables-UIQBtpmqYOs.pt-BR.vtt
3.3 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-MlE3BuOvWnU.zh-CN.vtt
3.3 kB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/06. Appending And NumPy-fdpKvovBMe4.zh-CN.vtt
3.3 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/10. NumPy Index Arrays-MlE3BuOvWnU.zh-CN.vtt
3.3 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/18. Joining Subqueries-rxy-fE5GeLY.en.vtt
3.3 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/08. Calculating Correlation-yLql7kR_6GE.en.vtt
3.3 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/08. Calculating Correlation-yLql7kR_6GE.en.vtt
3.3 kB
Part 12-Module 02-Lesson 05_Trees/15. Heaps-M3B0UJWS_ag.en-US.vtt
3.3 kB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.en.vtt
3.3 kB
Part 16-Module 03-Lesson 01_Basic SQL/06. Why Do Analysts Like SQL-uCNOtUht2Xc.pt-BR.vtt
3.3 kB
Part 18-Module 02-Lesson 01_Gathering Data/22. Why Do Analysts Like SQL-uCNOtUht2Xc.pt-BR.vtt
3.3 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/03. The Benefits of Interactivity-fIIyFYQyGLk.en.vtt
3.3 kB
Part 12-Module 02-Lesson 05_Trees/15. Heaps-M3B0UJWS_ag.en.vtt
3.3 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather CSV Files-FpWi4tExVwg.ar.vtt
3.3 kB
Part 05-Module 02-Lesson 03_Elements of SQL/10. Why Do It in the Database-6vfZYhhmuLU.ar.vtt
3.3 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/31. Data Join with a Key Function-ue_TULswM1Y.en.vtt
3.3 kB
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.th.vtt
3.3 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/09. Investigating the Data-zJ_wWRTQUTs.en.vtt
3.3 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/06. Accessing Elements of a DataFrame-hZp9cVuiPo0.en.vtt
3.3 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/13. Where's the Data-rHQ8z4fIthA.en.vtt
3.3 kB
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.pt-BR.vtt
3.3 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/06. Accessing Elements of a DataFrame-hZp9cVuiPo0.en.vtt
3.3 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Solution -lJEMTES2Ar8.ar.vtt
3.3 kB
Part 11-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.ar.vtt
3.3 kB
Part 13-Module 01-Lesson 07_Narrative Structures/48. Adding the Axes to the Page-B3qrRUamyUs.ar.vtt
3.3 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/14. Procedure-6rSJRr9OtHM.en.vtt
3.3 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-qsWz7r8muII.zh-CN.vtt
3.3 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/18. Debugging Data Analysis Code -l1pZZKsESAc.zh-CN.vtt
3.3 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/08. Unit of Analysis vs. Unit of Diversion-rzim0wu_0kM.pt-BR.vtt
3.3 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/14. Helpful Symbols-w4_8YCp-9fI.en.vtt
3.3 kB
Part 03-Module 01-Lesson 20_L8 Estimation/23. CI Bounds-6MdZ5NUfen0.en.vtt
3.3 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/18. Combining Pandas DataFrames-vB_Et1hz_2M.ar.vtt
3.3 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/18. Combining Pandas DataFrames-vB_Et1hz_2M.ar.vtt
3.3 kB
Part 18-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces) 2-tobH58uO24U.zh-CN.vtt
3.3 kB
Part 04-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.pt-BR.vtt
3.3 kB
Part 13-Module 01-Lesson 05_Dimple.js/34. Summary of Dimple and Chart Types-OrdADko3k1Q.pt-BR.vtt
3.3 kB
Part 16-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.pt-BR.vtt
3.3 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.ar.vtt
3.3 kB
Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-x-8-2zy8gmI.pt-BR.vtt
3.3 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-vuu3BY7X9ps.ar.vtt
3.3 kB
Part 17-Module 01-Lesson 08_Python Probability Practice/04. Simulating Many Coin Flips-AqpWQIj2V5Y.en.vtt
3.3 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/08. Whitespace-UxkIwcOczQQ.pt-BR.vtt
3.3 kB
Part 13-Module 01-Lesson 04_Design Principles/07. Small Multiples-HS_dsOQfwz8.zh-CN.vtt
3.3 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values-l3ergsxocok.en.vtt
3.3 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/20. Absolute or Relative Difference-TNcT_v2g3OQ.pt-BR.vtt
3.3 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values-l3ergsxocok.en.vtt
3.3 kB
Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-wPI9WOfpZbM.en.vtt
3.3 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/27. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.en.vtt
3.3 kB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.en.vtt
3.3 kB
Part 19-Module 01-Lesson 02_Design/03. Exploratory vs. Explanatory Analysis-wvgBSMks4p8.zh-CN.vtt
3.3 kB
Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys-fnbLMcd0FGQ.en.vtt
3.3 kB
Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-OzPNbN4L_L0.ar.vtt
3.3 kB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/05. Writing the Body-aK9Qnv3a6Wg.es-MX.vtt
3.3 kB
Part 09-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data-8FD_iOP24UA.en.vtt
3.3 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/26. Confidence Interval Case Breakdown-6pGDwrJHitw.zh-CN.vtt
3.3 kB
Part 16-Module 03-Lesson 02_SQL Joins/18. JOINs and Filtering-aI1kbDDNs4w.zh-CN.vtt
3.3 kB
Part 11-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data-x2dmBUEKQIA.ja.vtt
3.3 kB
Part 13-Module 01-Lesson 04_Design Principles/54. The Spectrum of Tech in Data Vis-4-tLvLvX9U4.ar.vtt
3.3 kB
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.pt-BR.vtt
3.3 kB
Part 11-Module 01-Lesson 09_Clustering/01. Unsupervised Learning-Mx9f99bRB3Q.en.vtt
3.3 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/12. Drawing and Altering the Map-soflPyVhb6o.pt-BR.vtt
3.3 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/20. Plotting With Pandas-kR7KZFqciFE.en.vtt
3.3 kB
Part 13-Module 01-Lesson 04_Design Principles/19. Pre-attentive Attributes-6UvLbIX0NQ4.en.vtt
3.3 kB
Part 11-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.ar.vtt
3.3 kB
Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-YbVuN2KOlt4.zh-CN.vtt
3.3 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/09. Investigating the Data-zJ_wWRTQUTs.pt-BR.vtt
3.3 kB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.es-MX.vtt
3.3 kB
Part 13-Module 01-Lesson 07_Narrative Structures/11. Personal Data Visualization-NtFICAw7tW4.ar.vtt
3.3 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.ar.vtt
3.3 kB
Part 12-Module 02-Lesson 02_List-Based Collections/11. Queues-XAbzlilAHZw.en-US.vtt
3.3 kB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/16. Type And Quality Plot - Part 1-iRCS1sE78KI.pt-BR.vtt
3.3 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/02. Intro to XML-eIVifBVJQIw.zh-CN.vtt
3.3 kB
Part 12-Module 02-Lesson 02_List-Based Collections/11. Queues-XAbzlilAHZw.en.vtt
3.3 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-iJEBxsKDDoE.pt-BR.vtt
3.3 kB
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-_7Vqou7k7fI.ar.vtt
3.3 kB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/01. Intro-vek87HVWexE.ar.vtt
3.3 kB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/01. Intro-vek87HVWexE.ar.vtt
3.3 kB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.pt-BR.vtt
3.3 kB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/01. Course Introduction-NKBUbUiedzc.pt-BR.vtt
3.3 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/10. Inspect GeoJSON-ThA4r4nzyj4.pt-BR.vtt
3.3 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/06. CSV Format-ra93hy88cok.en.vtt
3.3 kB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/11. CAST-LbyOq4ofLng.pt-BR.vtt
3.3 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -CSW2i2jIqyA.en.vtt
3.3 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts-zbjRiYSSR_Y.pt-BR.vtt
3.3 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/18. Joining Subqueries-rxy-fE5GeLY.pt-BR.vtt
3.3 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/13. Population vs. Cohort-HC2dunMuVW4.pt-BR.vtt
3.3 kB
Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-9JfaMZcSlQA.zh-CN.vtt
3.3 kB
Part 05-Module 01-Lesson 05_Data Quality/19. More About Correcting Data-vWBMgSQvsVk.en.vtt
3.3 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.ar.vtt
3.3 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/16. Type Type Conversion-yN6Fam_vZrU.en.vtt
3.3 kB
Part 21-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.pt-BR.vtt
3.3 kB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/09. Reviewing our Street Name Audit-eIvm5rEMZGY.zh-CN.vtt
3.3 kB
Part 18-Module 04-Lesson 01_Cleaning Data/11. Cleaning For Tidiness -6nMKFhpVCRU.en.vtt
3.3 kB
Part 13-Module 01-Lesson 07_Narrative Structures/19. Viewer-driven Examples-ft07qc8rTwM.en.vtt
3.3 kB
Part 17-Module 01-Lesson 08_Python Probability Practice/02. Simulating Coin Flips-7YtQNZ3iy6o.zh-CN.vtt
3.3 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. Performance Tuning 1-5mVfYZ_bfRo.pt-BR.vtt
3.3 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -Y288CGrwGy4.pt-BR.vtt
3.3 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/19. Plotting for DataFrames-CDVgPA0Mv2o.zh-CN.vtt
3.3 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/19. Plotting for DataFrames-CDVgPA0Mv2o.zh-CN.vtt
3.3 kB
Part 11-Module 01-Lesson 13_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.en.vtt
3.3 kB
Part 16-Module 03-Lesson 01_Basic SQL/43. AND BETWEEN Operators-nBuDPneWcKY.ar.vtt
3.3 kB
Part 05-Module 01-Lesson 05_Data Quality/17. Consistency-_5AnMdslWg4.en.vtt
3.2 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/05. Introduction to D3-mP1P0ybdZqI.zh-CN.vtt
3.2 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-WkInrWZwbNA.ar.vtt
3.2 kB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/23. Interpreting Interactions-XV6S2srsdxw.pt-BR.vtt
3.2 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. Performance Tuning 1-5mVfYZ_bfRo.en.vtt
3.2 kB
Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-TjY0Q66Yh-s.en.vtt
3.2 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/19. Sizing Triggering-ae9SWJxGM0w.en.vtt
3.2 kB
Part 14-Module 01-Lesson 05_Analyzing Results/11. Gotchas Simpson’s Paradox-GSPTcqNpab8.pt-BR.vtt
3.2 kB
Part 12-Module 02-Lesson 04_Maps and Hashing/09. String Keys-WyFwieF1NN4.en-US.vtt
3.2 kB
Part 11-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary-gBwGPI0srBE.en.vtt
3.2 kB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/01. Course Introduction-NKBUbUiedzc.en-US.vtt
3.2 kB
Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.pt-BR.vtt
3.2 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/13. Where's the Data-rHQ8z4fIthA.pt-BR.vtt
3.2 kB
Part 12-Module 02-Lesson 04_Maps and Hashing/09. String Keys-WyFwieF1NN4.en.vtt
3.2 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Introduction to Summary Statistics-PCZmHCrcMcw.ar.vtt
3.2 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/02. Lesson Overview-1EzlGH4Biu0.ar.vtt
3.2 kB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/01. Course Introduction-NKBUbUiedzc.en.vtt
3.2 kB
Part 18-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment Solution-H50mPHHp6fY.en.vtt
3.2 kB
Part 12-Module 02-Lesson 05_Trees/09. Insert-j6PkPa2ZHWg.en-US.vtt
3.2 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/01. Introduction to Course-gR_buSP6sdw.pt-BR.vtt
3.2 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/02. Tuskegee and Milgram Experiments-mxNp8_3syVk.ar.vtt
3.2 kB
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.pt-BR.vtt
3.2 kB
Part 12-Module 02-Lesson 05_Trees/09. Insert-j6PkPa2ZHWg.en.vtt
3.2 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/27. What If Our Sample Is Large-WoTCeSTL1eM.en.vtt
3.2 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/20. Plotting With Pandas-kR7KZFqciFE.zh-CN.vtt
3.2 kB
Part 05-Module 02-Lesson 05_Deeper into SQL/08. Declaring Relationships-1FjqstT1faI.en.vtt
3.2 kB
Part 12-Module 02-Lesson 06_Graphs/10. DFS-BC8jEidd2EQ.pt-BR.vtt
3.2 kB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/04. Statistical Significance-kpdwHL54eys.zh-CN.vtt
3.2 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/08. Overview of Business Example-tlSe7H9BDy8.zh-CN.vtt
3.2 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size-4-MF0UZac8o.zh-CN.vtt
3.2 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-JqyUT7RbvgI.pt-BR.vtt
3.2 kB
Part 13-Module 01-Lesson 07_Narrative Structures/42. I Love Data Visualization-j24CoLV675I.ar.vtt
3.2 kB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/03. Your First Subquery-cTM1jPYXLoQ.pt-BR.vtt
3.2 kB
Part 11-Module 01-Lesson 09_Clustering/01. Unsupervised Learning-Mx9f99bRB3Q.pt-BR.vtt
3.2 kB
Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.ar.vtt
3.2 kB
Part 11-Module 01-Lesson 16_Tying It All Together/04. Outro-VCNcNnZ6V_s.ar.vtt
3.2 kB
Part 13-Module 01-Lesson 07_Narrative Structures/24. Annotations World Cup Attendance Chart-Aq39o9xrW5A.zh-CN.vtt
3.2 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/03. Two-Dimensional NumPy Arrays-UFcCmB7Xvvs.zh-CN.vtt
3.2 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/03. Two-Dimensional NumPy Arrays-UFcCmB7Xvvs.zh-CN.vtt
3.2 kB
Part 13-Module 01-Lesson 07_Narrative Structures/17. Different Types of Narrative Structures-vTlpDo33ezg.en.vtt
3.2 kB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/23. Interpreting Interactions-XV6S2srsdxw.en.vtt
3.2 kB
Part 13-Module 01-Lesson 07_Narrative Structures/13. Errors in Data Collection-xcYDjXpYbs0.zh-CN.vtt
3.2 kB
Part 07-Module 01-Lesson 01_GitHub Review/02. GitHub profile important items-prvPVTjVkwQ.pt-BR.vtt
3.2 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/45. Fixing the Buttons-NxM_iu4sDxw.pt-BR.vtt
3.2 kB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.pt-BR.vtt
3.2 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.pt-BR.vtt
3.2 kB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.ja.vtt
3.2 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-6CiZB0N7y64.pt-BR.vtt
3.2 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-6CiZB0N7y64.pt-BR.vtt
3.2 kB
Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-FT0dM2um34E.ar.vtt
3.2 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.ar.vtt
3.2 kB
Part 11-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter-m2a2K4lprQw.pt-BR.vtt
3.2 kB
Part 09-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data-8FD_iOP24UA.ja.vtt
3.2 kB
Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-oEhevl5DWpk.zh-CN.vtt
3.2 kB
Part 12-Module 02-Lesson 08_Technical Interview - Python/09. Debugging-Bz1tlvkql9Q.zh-CN.vtt
3.2 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/29. Why D3-2qZ3d2WOvwE.ar.vtt
3.2 kB
Part 17-Module 01-Lesson 11_Confidence Intervals/08. Statistical vs. Practical Differences-RKHD1wzxxPA.en.vtt
3.2 kB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.en.vtt
3.2 kB
Part 12-Module 01-Lesson 05_Interview Practice/07. Jimmy's Analysis of the Interview-wg535YU4jFw.en.vtt
3.2 kB
Part 09-Module 01-Lesson 01_What is EDA/05. Goals of EDA-NEvuulahg2g.ja.vtt
3.2 kB
Part 16-Module 03-Lesson 03_SQL Aggregations/13. GROUP BY-9vb67TF4WV0.en.vtt
3.2 kB
Part 21-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.ar.vtt
3.2 kB
Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.pt-BR.vtt
3.2 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/23. Nonparametric Answers-Z0QcZHrflmc.zh-CN.vtt
3.2 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-WnQoZzxas-g.ar.vtt
3.2 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/12. Drawing and Altering the Map-soflPyVhb6o.en.vtt
3.2 kB
Part 05-Module 02-Lesson 01_Data and Tables/10. How Queries Happen-v3EkXogyIL4.pt-BR.vtt
3.2 kB
Part 12-Module 01-Lesson 03_Interview Fails/03. Interviewing Fails Siya Raj Purohit-wYop-N5YgeA.pt-BR.vtt
3.2 kB
Part 14-Module 01-Lesson 05_Analyzing Results/08. Single Metric Introduction-StP9L9f70EU.en.vtt
3.2 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/04. Assessing the Quality of Data Pt. 2-8onBHqvvrig.zh-CN.vtt
3.2 kB
Part 11-Module 01-Lesson 10_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.pt-BR.vtt
3.2 kB
Part 12-Module 02-Lesson 05_Trees/15. Heaps-M3B0UJWS_ag.pt-BR.vtt
3.2 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.pt-BR.vtt
3.2 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.pt-BR.vtt
3.2 kB
Part 13-Module 01-Lesson 05_Dimple.js/20. Object Oriented Design and Charts-2uzNpGWdavc.pt-BR.vtt
3.2 kB
Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 Solution-kqcuw1qCLEM.en.vtt
3.2 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Calculating the Mean-1nzZxmJ8xvU.ar.vtt
3.2 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/02. Unit of Diversion Overview-Gh32VbXrmdQ.en.vtt
3.2 kB
Part 19-Module 01-Lesson 02_Design/05. What Makes a Bad Visual-zbvB_9f7bFs.zh-CN.vtt
3.2 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/01. What is Data Visualization-mfLklbVU7r0.ar.vtt
3.2 kB
Part 13-Module 01-Lesson 07_Narrative Structures/41. Parsing Data Before the Draw Function-WALbqgiDHNI.en.vtt
3.2 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/09. Types Of Errors - Part II-mbdSQ5CjdFs.en.vtt
3.2 kB
Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-YZb-Uam-Ics.pt-BR.vtt
3.2 kB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/07. Efficiency-I-RASDPbDrI.zh-CN.vtt
3.2 kB
Part 03-Module 01-Lesson 11_L4 Variability/35. Point of SD-d-_ZKyocTDw.ar.vtt
3.2 kB
Part 05-Module 02-Lesson 01_Data and Tables/02. What's a Database - Intro to Relational Databases-V4gbPVdUOpw.pt-BR.vtt
3.2 kB
Part 12-Module 01-Lesson 03_Interview Fails/03. Interviewing Fails Siya Raj Purohit-wYop-N5YgeA.en.vtt
3.2 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/13. Metric Definition Example-1EoJTK_S0mk.zh-CN.vtt
3.2 kB
Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-lWjaCJazJE0.ar.vtt
3.2 kB
Part 13-Module 01-Lesson 04_Design Principles/51. D3 Functions-4OkB_Ybo0i0.zh-CN.vtt
3.2 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/20. Clean Define-qHB4jsqcfi4.zh-CN.vtt
3.2 kB
Part 21-Module 01-Lesson 03_Control Flow/02. If Statements-jWiIUMrwPqA.pt-BR.vtt
3.2 kB
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-HEnJRwJ23us.pt-BR.vtt
3.2 kB
Part 16-Module 03-Lesson 01_Basic SQL/40. NOT Operator-dSQF87oW8a0.ar.vtt
3.2 kB
Part 09-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.ar.vtt
3.2 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/10. Inspect GeoJSON-ThA4r4nzyj4.en.vtt
3.2 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/16. Assess Programmatic-6JubHCD7dh4.en.vtt
3.2 kB
Part 13-Module 01-Lesson 07_Narrative Structures/62. Adding Circles to the Legend-FlbCPYGCKqk.zh-CN.vtt
3.2 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/19. Sizing Triggering-ae9SWJxGM0w.pt-BR.vtt
3.2 kB
Part 21-Module 01-Lesson 05_Scripting/26. Third Party Libraries And Package Managers-epOze9gC6T4.zh-CN.vtt
3.2 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/02. Problems Solved by Data Analysts-jZEbCVZzwUk.en.vtt
3.2 kB
Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-80aFO4KmcPM.ar.vtt
3.2 kB
Part 13-Module 01-Lesson 07_Narrative Structures/56. Recap and Data Dependency-00Tz_3_91RU.pt-BR.vtt
3.2 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-hmhlyOVAVOs.en.vtt
3.2 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-hmhlyOVAVOs.pt-BR.vtt
3.2 kB
Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-jkJ4dbbpVCQ.zh-CN.vtt
3.2 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/13. Population vs. Cohort-HC2dunMuVW4.en.vtt
3.2 kB
Part 11-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter-m2a2K4lprQw.en.vtt
3.2 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/02. Data Modeling in MongoDB-6sDkIE_nAGI.zh-CN.vtt
3.2 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/23. Making Histograms-0J5lNTGbspg.zh-CN.vtt
3.2 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/29. Formula for Location of Median-lNYLU1b4qoM.en.vtt
3.2 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.ar.vtt
3.2 kB
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-vLlj5nNj8x4.pt-BR.vtt
3.2 kB
Part 17-Module 01-Lesson 13_Case Study AB tests/02. AB Testing-EcWvhbIjT9o.en.vtt
3.2 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.ar.vtt
3.2 kB
Part 09-Module 01-Lesson 01_What is EDA/05. Goals of EDA-NEvuulahg2g.pt-BR.vtt
3.2 kB
Part 13-Module 01-Lesson 04_Design Principles/35. Chartjunk-jm2qOX2Q2HQ.ar.vtt
3.2 kB
Part 15-Module 01-Lesson 02_Design Principles/16. Gráfico Lixo-jm2qOX2Q2HQ.ar.vtt
3.2 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/23. McDonald's-29Vf6PytVbA.es.vtt
3.2 kB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/23. McDonald's-29Vf6PytVbA.es.vtt
3.2 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.zh-CN.vtt
3.2 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.zh-CN.vtt
3.2 kB
Part 13-Module 01-Lesson 07_Narrative Structures/50. The Anonymous Accessor Function-I4niz8YMMUM.ar.vtt
3.2 kB
Part 16-Module 03-Lesson 01_Basic SQL/11. SELECT FROM Statements-urOYuuav4BY.zh-CN.vtt
3.2 kB
Part 18-Module 02-Lesson 01_Gathering Data/22. SELECT FROM Statements-urOYuuav4BY.zh-CN.vtt
3.2 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/06. Accessing Elements of a DataFrame-4RmQYWI8lY4.zh-CN.vtt
3.2 kB
Part 12-Module 01-Lesson 03_Interview Fails/03. Interviewing Fails Siya Raj Purohit-wYop-N5YgeA.es-MX.vtt
3.2 kB
Part 16-Module 03-Lesson 02_SQL Joins/14. JOINs-CxuHtd1Daqk.ar.vtt
3.2 kB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/02. Cleaning with String Functions-y1fduSu7Ovc.en.vtt
3.2 kB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML and Trees-766JMEtZCPE.ar.vtt
3.2 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/06. Accessing Elements of a DataFrame-4RmQYWI8lY4.zh-CN.vtt
3.2 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1-J4X9r0EGH3k.pt-BR.vtt
3.2 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/05. Tabular Formats-5Vq530Lijb0.ar.vtt
3.1 kB
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.ja.vtt
3.1 kB
Part 13-Module 01-Lesson 07_Narrative Structures/47. Creating Axes-3jEbyeW1Re4.ar.vtt
3.1 kB
Part 16-Module 03-Lesson 02_SQL Joins/18. JOINs and Filtering-aI1kbDDNs4w.pt-BR.vtt
3.1 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-iJEBxsKDDoE.en.vtt
3.1 kB
Part 14-Module 01-Lesson 05_Analyzing Results/02. Sanity Checks-OVnlC_T3EpI.en.vtt
3.1 kB
Part 21-Module 01-Lesson 05_Scripting/21. The Standard Library-Fw3vf0tDrJM.en.vtt
3.1 kB
Part 16-Module 03-Lesson 02_SQL Joins/02. Why Use Separate Tables-UIQBtpmqYOs.en.vtt
3.1 kB
Part 17-Module 01-Lesson 14_Regression/06. Scatter Plots -DvlxZ37O4i8.ar.vtt
3.1 kB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/09. Scatter Plots -DvlxZ37O4i8.ar.vtt
3.1 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/19. String Methods-Bv7CAxVOONs.zh-CN.vtt
3.1 kB
Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-OB7iJnEY0Tg.ar.vtt
3.1 kB
Part 13-Module 01-Lesson 07_Narrative Structures/03. Correlation vs Causation-8u96-UEf_ms.pt-BR.vtt
3.1 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/23. Drawing Conclusions Example-yAl58ccwyvU.pt-BR.vtt
3.1 kB
Part 17-Module 01-Lesson 13_Case Study AB tests/11. Metric - Average Reading Duration-w6Y9ZxHDEbw.pt-BR.vtt
3.1 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/12. Gathering Data-JsVg95-amjI.zh-CN.vtt
3.1 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/05. Intro to CSVs-UFiJYYPL95g.en.vtt
3.1 kB
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.ja.vtt
3.1 kB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/03. Dijkstra's Algorithm-SoPMK03cOgk.zh-CN.vtt
3.1 kB
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.pt-BR.vtt
3.1 kB
Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.ar.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/03. Data Types and NULLs-RgTcYwKqtYI.ar.vtt
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.en.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-B_fHrMIzIgE.ar.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-OurfO1ZR2GU.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/31. Red Green Color Blindness-iqbqj9kbapM.ar.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/12. Projection Queries-dFGlIC9nI1Q.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/02. Unit of Diversion Overview-Gh32VbXrmdQ.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/15. Nest Function-rwDTbptCnM4.ar.vtt
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Part 19-Module 01-Lesson 02_Design/15. Shape, Size, and other Tools-fzEliHW3ZLM.zh-CN.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/06. Why Businesses Choose Databases-j4ey7--h9r8.ar.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/22. Why Businesses Choose Databases-j4ey7--h9r8.ar.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment Solution-H50mPHHp6fY.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -Y288CGrwGy4.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/07. DF - Sample SD-Jfk3egev9UM.pt-BR.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/04. Fitting Logistic Regression In Python-baQf-XiZQQ4.en.vtt
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Part 11-Module 01-Lesson 13_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/55. Attendance at Every World Cup Game-LuCV0YuhoZE.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.en.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/25. DATE Functions I-E7Z6GMFVmIY.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/12. Target Population Example-XsyavvSGjLM.zh-CN.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -exMGBx6Rs_E.en.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-7CVlKQ3UjUI.pt-BR.vtt
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Part 12-Module 02-Lesson 06_Graphs/13. Eulerian Path-zS34kHSo7fs.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/20. Object Oriented Design and Charts-2uzNpGWdavc.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.ar.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.en.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.en.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.en.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/27. Empirical Variability Bootstrapping-YW-uud_btQ8.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/22. Comparing the Two Student Groups-eM82u21V7AM.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/25. Communicating with Color-QnFtYKXf7TQ.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-dtnjREsGfXI.en.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-LlPsmQx5y50.ar.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/30. Code Structure and JavaScript-vPCDvEOjP7c.en.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/07. Visual Assessment -GVVibuIg3Ro.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/39. Clarifying Sample SD-iRudjk53deY.ar.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/02. Twitter Data Set-xiqleK_px_Q.zh-CN.vtt
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Part 11-Module 01-Lesson 09_Clustering/10. K-Means Clustering Visualization 2-fQXXa-CAoS0.zh-CN.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/08. Efficiency of Bubble Sort-KddkHygi7is.zh-CN.vtt
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Part 21-Module 01-Lesson 03_Control Flow/20. L3 08 While Loops V3-7Sf5tcPlKQw.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/12. Factor Variables-0bkvt4KEqjE.en.vtt
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/06. Dynamic Programming-VQeFcG9pjJU.zh-CN.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather Intro-K5ITQn1L1R0.ar.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/11. Gotchas Simpson’s Paradox-GSPTcqNpab8.zh-CN.vtt
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Part 17-Module 01-Lesson 14_Regression/13. Fitting A Regression Line-xQob80zrT3s.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/17. Collecting Stadium Locations-CqE3Zqv21Wo.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.en.vtt
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Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-NjuenhkC-44.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.ar.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/30. Code Structure and JavaScript-vPCDvEOjP7c.pt-BR.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.ar.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/06. Intro to Sorting-Z6yuIen71zM.en-US.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/17. Aggregations-4nGL3y3Nq-0.pt-BR.vtt
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Part 11-Module 01-Lesson 11_Text Learning/14. Why Upweight Rare Words-xYQb6f1SIEk.ar.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. More on Performance Tuning-ZK1FvNH10Ag.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -oWu4UDkPmj8.ar.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/13. Text File Structure-O4qEWpXZLQg.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-paj5z9U1OBk.en.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/09. String Keys-WyFwieF1NN4.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-dtnjREsGfXI.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/14. Procedure-6rSJRr9OtHM.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/61. I am Legend-EdiM9XCqc0Y.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/61. I am Legend-EdiM9XCqc0Y.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/64. All World Cup Games Recap-tVtEEL5i_BE.ar.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/27. What If Our Sample Is Large-WoTCeSTL1eM.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.it.vtt
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Part 12-Module 02-Lesson 01_Introduction and Efficiency/09. Notation Continued-ZeGnkrKZWBQ.pt-BR.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/05. Hashing-kCPFfHx_LgQ.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-Q2M8xyY47fc.en.vtt
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Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-DxCwtkrYR-s.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.es.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/32. Binding Data-yW9LEMFOzgY.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/25. Sorting the Data for Drawing Order-X-zVfcuacD4.ar.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-6CiZB0N7y64.en.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-6CiZB0N7y64.en.vtt
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Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-XDvus8zHJbA.ar.vtt
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Part 17-Module 01-Lesson 08_Python Probability Practice/04. Simulating Many Coin Flips-AqpWQIj2V5Y.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-fRNDqy-le8U.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-TjY0Q66Yh-s.ja.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.ar.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/06. Interpreting Multiplie Linear Regression Coefficients-qRD3OVX8UMM.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/45. Fixing the Buttons-NxM_iu4sDxw.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/01. Introduction to Course-gR_buSP6sdw.en.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/31. Small Multiples And Dual Axis-bx6MxsoDqsI.ar.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.ar.vtt
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Part 09-Module 01-Lesson 02_R Basics/12. Factor Variables-0bkvt4KEqjE.ja.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/10. Welcome to the end of the lesson-nWFJ_eOU27I.zh-CN.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-f7vNKm0Zci0.ar.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/02. Sanity Checks-OVnlC_T3EpI.pt-BR.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators-48AgxPygRuQ.ar.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/04. Fitting Logistic Regression In Python-baQf-XiZQQ4.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/10. How Queries Happen-v3EkXogyIL4.en.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/24. WHERE Statements -mN0uTnlXaxg.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/26. Where are we-d3jQdOuOy8k.ar.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/11. Traditional vs. Bootstrapping Confidence Intervals-eZ8lyiumXDY.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/12. DataFrame apply()-KSZ2XLYk4hk.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-E3NhvAC3Ghw.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/22. Encoding Nothing-6bpET1lWVtA.pt-BR.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/09. Types Of Errors - Part II-mbdSQ5CjdFs.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/12. DataFrame apply()-KSZ2XLYk4hk.zh-CN.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/26. Klout-3q0oPuWxFpA.pt-BR.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/13. Binomial Distribution-PVTChqpnr5Q.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.es-ES.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/03. Types in the SQL World-8swA-PqlEP0.ar.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/08. Whitespace-UxkIwcOczQQ.en.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/08. Addressing Missing Data First -ArAGZCUMj9Q.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/03. Correlation vs Causation-8u96-UEf_ms.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-wPI9WOfpZbM.zh-CN.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-qgwygpD0eN8.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.zh-CN.vtt
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Part 09-Module 01-Lesson 02_R Basics/12. Factor Variables-0bkvt4KEqjE.pt-BR.vtt
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Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-DxCwtkrYR-s.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax-7XyFjPDPoZQ.en.vtt
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/06. 04 Aggregation Granularity-GuOytlkqdrQ.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/15. SD of Karma Points per Post-uCRzrlaA8mg.pt-BR.vtt
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Part 21-Module 01-Lesson 05_Scripting/05. Running A Python Script-vMKemwCderg.ar.vtt
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Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-NjuenhkC-44.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/23. Changing the Date Format-_jOLSNoKxhQ.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.th.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/19. Lessons Learned-5JjCVTc0FGk.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/media/exampleTextPositioning.svg
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Part 02-Module 01-Lesson 01_Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.th.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.th.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/21. Variability-1KmFcGt6Uo0.pt-BR.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/02. Arithmetic Operators-M8TIOK2P2yw.zh-CN.vtt
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Part 21-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.pt-BR.vtt
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Part 19-Module 01-Lesson 02_Design/07. Chart Junk-3BTBEYOG2o8.ar.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-fo4MJMkwhYU.zh-CN.vtt
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Part 11-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.ar.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Solution --faitcQ7SKs.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps-zSSNWZuVG8Y.ja.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/43. D3 Parsing Dates and Times-DrOoJJWRAno.zh-CN.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/18. Joining Subqueries-rxy-fE5GeLY.zh-CN.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/12. Which Distribution-tTb1k27rhgI.ar.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/08. Standard Deviation Calculation-H5zA1A-XPoY.zh-CN.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/22. Scraping Solution-J1gn4ZBLkt4.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/40. Smoothing the Animation with Transitions-9c8he26k_iY.en.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/19. Using Beautiful Soup-_rDjie-TaS8.pt-BR.vtt
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Part 21-Module 01-Lesson 05_Scripting/13. Handling Errors Try Except Finally-S6hwBZG0KwM.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-74mudn321tA.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/19. Viewer-driven Examples-ft07qc8rTwM.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/06. Interval Estimate for Population Mean-ECRw3cSiy6o.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/01. t-Distribution-N6wKbV1DVos.en.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/11. Gotchas Simpson’s Paradox-Tx_jtCfrbt0.zh-CN.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.ar.vtt
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/06. 04 Aggregation Granularity-GuOytlkqdrQ.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/31. Data Join with a Key Function-ue_TULswM1Y.zh-CN.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/06. Types vs. Steps -oZmndg-BnPk.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-WCcnGQY771c.ar.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/07. Aggregation Operators 2-UZMklqP5-p4.ar.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-WCcnGQY771c.ar.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-JqyUT7RbvgI.en.vtt
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Part 12-Module 02-Lesson 02_List-Based Collections/11. Queues-XAbzlilAHZw.pt-BR.vtt
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Part 17-Module 01-Lesson 13_Case Study AB tests/05. Experiment I-JLKAdT2JESk.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-YPPQy_eB2mU.ar.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-HEnJRwJ23us.en.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/16. Type Type Conversion-yN6Fam_vZrU.zh-CN.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/26. Updates-mpMHJQalRck.zh-CN.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment Solution-LhdGQC_vjEs.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/04. Install RStudio on Windows-5ZbjUEg4a1g.zh-CN.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/17. Shape of Distributions-UnN99AAYf8k.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-vLlj5nNj8x4.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-hfmvk8DzTGA.pt-BR.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/12. Types Of Errors - Part III-Z-srkCPsdaM.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-jKZAcZw9xLA.ar.vtt
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Part 11-Module 01-Lesson 16_Tying It All Together/02. Summary-avqZaTECZTQ.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-K6zJtrTEf6k.pt-BR.vtt
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Part 17-Module 01-Lesson 14_Regression/16. How Do We Interpret Results-eLk0XGGMaCE.pt-BR.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/06. Types vs. Steps -oZmndg-BnPk.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-BqQbAqok8JU.pt-BR.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/17. Shape of Distributions-UnN99AAYf8k.pt-BR.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-BqQbAqok8JU.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/21. Drone Strikes and Gun Deaths-_MXW29cfh_8.en.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/08. Single Metric Introduction-StP9L9f70EU.pt-BR.vtt
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Part 12-Module 02-Lesson 01_Introduction and Efficiency/09. Notation Continued-ZeGnkrKZWBQ.en-US.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/40. Smoothing the Animation with Transitions-9c8he26k_iY.pt-BR.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-7CVlKQ3UjUI.en.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/22. Random Observed Values-KFIt2OC3wCI.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/39. Using extent() for scales-oazLw2JhKiU.en.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/04. 29 Number Summary-gzUN5zKLHjQ.zh-CN.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/28. Assumptions-CdoWdNAKSYw.pt-BR.vtt
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Part 12-Module 02-Lesson 01_Introduction and Efficiency/09. Notation Continued-ZeGnkrKZWBQ.en.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts-zbjRiYSSR_Y.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys-fnbLMcd0FGQ.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-GtR3dw2eq2w.ar.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/02. GitHub profile important items-prvPVTjVkwQ.en.vtt
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Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-StmEUgT1XSY.ar.vtt
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Part 21-Module 01-Lesson 03_Control Flow/31. List Comprehensions-6qxo-NV9v_s.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-YaZu4waSryo.zh-CN.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/08. Efficiency of Bubble Sort-KddkHygi7is.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/29. Correcting Color-7vaHp4caWxw.ar.vtt
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Part 17-Module 01-Lesson 13_Case Study AB tests/07. Metric - Click Through Rate-EpfoKAwV_Eg.zh-CN.vtt
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Part 21-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.en.vtt
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/05. Cleaning With More Advanced String Functions-E6cK8RbYGEc.ar.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/16. Binomial Distribution Conclusion-9gjCYs8f_PU.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-PZSPhQCVABg.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-DclTt9xqS4s.ar.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/17. Aggregations-4nGL3y3Nq-0.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values-l3ergsxocok.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values-l3ergsxocok.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/23. CI Bounds-6MdZ5NUfen0.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/40. Lie Factor-jkR2kIJrvBM.ar.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-tfhsgVCX2Ao.ar.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/29. Removing Documents-oFWNOvxuIRQ.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax-7XyFjPDPoZQ.pt-BR.vtt
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Part 09-Module 01-Lesson 01_What is EDA/05. Goals of EDA-NEvuulahg2g.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/22. Simulation Applet-yu4mdXybrts.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.th.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/12. Creating and Drawing the Chart-ZyhYNaRqqL0.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/01. Dimple Interlude-bo8_lJucTPI.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/10. 95 CI with Exact Z-Scores-apqUAtnsLZE.pt-BR.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/12. Types Of Errors - Part III-Z-srkCPsdaM.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/34. DT Strengths and Weaknesses-KGnhg76iRfI.ja.vtt
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Part 12-Module 01-Lesson 03_Interview Fails/03. Interviewing Fails Siya Raj Purohit-wYop-N5YgeA.zh-CN.vtt
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Part 12-Module 02-Lesson 06_Graphs/10. DFS-BC8jEidd2EQ.zh-CN.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/13. Where's the Data-rHQ8z4fIthA.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/34. Summary of Dimple and Chart Types-OrdADko3k1Q.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/29. Collecting Participating Countries-ha6kGtT9XMQ.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data-8FD_iOP24UA.zh-CN.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-GXT_vXBA0vQ.zh-CN.vtt
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Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-OGK9SHt8SWg.ar.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-YZb-Uam-Ics.en.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/25. Aggregations-ADx1x2ljFB4.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1 Solution -I1enB5CA85Q.pt-BR.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/03. Unit of Diversion Example-_-BxFJTBNMM.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/12. Target Population Example-kEFp6xIb8cs.pt-BR.vtt
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/11. CAST-LbyOq4ofLng.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/63. Adding Text to the Legend-VPI9MVqGiSM.en.vtt
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/16. Type And Quality Plot - Part 1-iRCS1sE78KI.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/29. Data Analysis and Related Terms-9g9_tlhbNSw.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/09. Investigating the Data-zJ_wWRTQUTs.zh-CN.vtt
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Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/14. What is plot.ly-ZRiAWz-sVlM.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.ar.vtt
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/09. 06 Practice With Marks And Filters-RPAv7WLkutk.zh-CN.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/21. Working with Outliers-4RnQjtJB8t8.ar.vtt
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Part 21-Module 01-Lesson 05_Scripting/13. Handling Error Specifying Exceptions-EHW5I7shdJg.ar.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-AqlvTMZg6HY.es.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/01. Introduction-yod62-mxXR4.pt-BR.vtt
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Part 05-Module 01-Lesson 05_Data Quality/07. A Blueprint for Cleaning-3S73cNbhuAk.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.ar.vtt
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Part 21-Module 01-Lesson 03_Control Flow/31. List Comprehensions-6qxo-NV9v_s.zh-CN.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/06. Interpreting Multiplie Linear Regression Coefficients-qRD3OVX8UMM.pt-BR.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment Solution-H50mPHHp6fY.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.ar.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/01. Introduction-yod62-mxXR4.en-US.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/01. Introduction-yod62-mxXR4.en.vtt
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Part 21-Module 01-Lesson 01_Why Python Programming/04. L1 02 Course Overview V4-vFxXSIV5cHM.pt-BR.vtt
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Part 12-Module 02-Lesson 05_Trees/09. Insert-j6PkPa2ZHWg.pt-BR.vtt
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Part 12-Module 02-Lesson 05_Trees/15. Heaps-M3B0UJWS_ag.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/19. Pre-attentive Attributes-6UvLbIX0NQ4.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/25. Communicating with Color-QnFtYKXf7TQ.en.vtt
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Part 15-Module 01-Lesson 02_Design Principles/13. Communicating with Color-QnFtYKXf7TQ.en.vtt
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/04. Ways in the Open Street Map XML-1OwIbj9dcLo.pt-BR.vtt
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/05. Ways in the Open Street Map XML-1OwIbj9dcLo.pt-BR.vtt
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/01. Get an Interview with a Cover Letter!-BH1KY63YfAM.en.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/08. Self JOINs-tw_VzEGBOvI.ar.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/04. Algorithm Options-S-cGZ-FEdjQ.pt-BR.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/16. Lasso Regression-qU1_cj4LfLY.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/03. Good Data Visualization-ePekYbKs60U.zh-CN.vtt
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/03. Iterative Parsing-pxUvIP4PQt0.pt-BR.vtt
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/03. Iterative Parsing-pxUvIP4PQt0.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.it.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty Messy -WG6mil60jq0.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-R5EsIDJ0apw.ar.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/06. Why Do Analysts Like SQL-uCNOtUht2Xc.en.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/22. Why Do Analysts Like SQL-uCNOtUht2Xc.en.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. Performance Tuning 1-5mVfYZ_bfRo.zh-CN.vtt
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/03. Iterative Parsing-pxUvIP4PQt0.en.vtt
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/03. Iterative Parsing-pxUvIP4PQt0.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/34. DT Strengths and Weaknesses-KGnhg76iRfI.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/19. Using Beautiful Soup-_rDjie-TaS8.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps-zSSNWZuVG8Y.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.ar.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/03. Your First Subquery-cTM1jPYXLoQ.en.vtt
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Part 11-Module 01-Lesson 03_SVM/10. SVM in SKlearn-R7xQtQzkvTk.ja.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel-j5tA__Dq-sQ.ar.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/20. Calculating the p-value-_W3Jg7jQ8jI.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/08. Declaring Relationships-1FjqstT1faI.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax-7XyFjPDPoZQ.ja.vtt
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Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules Part II-aASigWQ_XU0.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-x-8-2zy8gmI.zh-CN.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/26. Klout-3q0oPuWxFpA.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-AaLIKufl_mY.pt-BR.vtt
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Part 12-Module 02-Lesson 05_Trees/19. Red-Black Trees - Insertion-dIuWLtWnkgs.en-US.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 Solution-kqcuw1qCLEM.pt-BR.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/23. Marks And Filters-FeYRmZHHu0A.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -CSW2i2jIqyA.zh-CN.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/15. What About More Than Two Variables -ufKcdUbLj9c.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-zovzbp_Rpu4.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.ja.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.ja.vtt
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Part 12-Module 02-Lesson 05_Trees/19. Red-Black Trees - Insertion-dIuWLtWnkgs.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/14. Helpful Symbols-w4_8YCp-9fI.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/26. Predicting Based on Many Features-oZqGlJbRZu4.pt-BR.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/09. String Keys-WyFwieF1NN4.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-K6zJtrTEf6k.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.en.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-9L9bhMCHQ-M.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/31. Customizing a Dimple Chart-93MgOnKP5m0.pt-BR.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/06. Other Techniques-KsiyW6bPux8.pt-BR.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-j0qfuunqym8.ar.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/06. CSVs in Python-YIDH9HBY3Qk.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/14. Loading Data with Nested Functions-ME6F4Nyjv8o.zh-CN.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/14. Procedure-6rSJRr9OtHM.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-bR7EoKjN0EM.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/24. MM CLT-DqC-pgcEam4.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/02. Course Format-rVmwPGFtk_Y.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-hfmvk8DzTGA.en.vtt
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Part 19-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings-98aog0eVcC4.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.th.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/03. How This Lesson Is Structured-xfRtO4aFpv0.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-5GYA5j1fqBU.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/10. Details of the Data Science Process-8TeiMKUmoYQ.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.ja.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.es-ES.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/01. Intro to MongoDB-GfK7GW3V-W0.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/21. Drone Strikes and Gun Deaths-_MXW29cfh_8.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.en.vtt
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Part 21-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-xsdj1qJwgk4.zh-CN.vtt
2.9 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-tGHQsk1SGGU.ar.vtt
2.9 kB
Part 16-Module 03-Lesson 03_SQL Aggregations/13. GROUP BY-9vb67TF4WV0.zh-CN.vtt
2.9 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/07. What is the Standard Deviation Measuring-IbwUJ3ORZ5s.pt-BR.vtt
2.9 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Solution -lJEMTES2Ar8.pt-BR.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/10. Boolean Comparison and Logical Operators-iNNsUJIDtVU.en.vtt
2.9 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/17. Aggregations-4nGL3y3Nq-0.zh-CN.vtt
2.9 kB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/03. Get to Know the PDF-52HAbu6_u9I.zh-CN.vtt
2.9 kB
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.en.vtt
2.9 kB
Part 12-Module 02-Lesson 03_Searching and Sorting/06. Intro to Sorting-Z6yuIen71zM.pt-BR.vtt
2.9 kB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/04. Ways in the Open Street Map XML-1OwIbj9dcLo.en.vtt
2.9 kB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/05. Ways in the Open Street Map XML-1OwIbj9dcLo.en.vtt
2.9 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-Q2M8xyY47fc.zh-CN.vtt
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Part 12-Module 02-Lesson 05_Trees/09. Insert-j6PkPa2ZHWg.zh-CN.vtt
2.9 kB
Part 17-Module 01-Lesson 16_Logistic Regression/02. Fitting Logistic Regression-Dg0rBDQnIYg.pt-BR.vtt
2.9 kB
Part 11-Module 01-Lesson 09_Clustering/02. Clustering Movies-g8PKffm8IRY.pt-BR.vtt
2.9 kB
Part 13-Module 01-Lesson 04_Design Principles/22. Encoding Nothing-6bpET1lWVtA.en.vtt
2.9 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/06. Other Techniques-KsiyW6bPux8.en.vtt
2.9 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.pt-BR.vtt
2.9 kB
Part 21-Module 01-Lesson 05_Scripting/13. Handling Errors Try Except Finally-S6hwBZG0KwM.zh-CN.vtt
2.9 kB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/06. Resume Review-L3F2BFGYMtI.pt-BR.vtt
2.9 kB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/06. Resume Review-L3F2BFGYMtI.pt-BR.vtt
2.9 kB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/06. Resume Review-L3F2BFGYMtI.pt-BR.vtt
2.9 kB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/04. Algorithm Options-S-cGZ-FEdjQ.en.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2-Vvzl2J5K7-Y.ar.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/46. OR Operator-3vLGEuXAAvA.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.ar.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-1Hd1Bq1YxXg.ar.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 Solution-kqcuw1qCLEM.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/01. Summary-51hx5u2EMZA.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-tfYAGBIR_Ws.pt-BR.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Notation for the Mean-3EF15AoRxyM.ar.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/16. Assess Programmatic-6JubHCD7dh4.zh-CN.vtt
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Part 05-Module 01-Lesson 05_Data Quality/17. Consistency-_5AnMdslWg4.zh-CN.vtt
2.9 kB
Part 12-Module 02-Lesson 02_List-Based Collections/11. Queues-XAbzlilAHZw.zh-CN.vtt
2.9 kB
Part 11-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/27. Defining a Join-Xo-OJXzS0tQ.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-paj5z9U1OBk.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-TjY0Q66Yh-s.zh-CN.vtt
2.9 kB
Part 13-Module 01-Lesson 04_Design Principles/36. Less is More-urgyRvfWPtU.en.vtt
2.9 kB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/15. Finches-ONhDQKYCJlE.pt-BR.vtt
2.9 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-BqQbAqok8JU.en.vtt
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Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files-w-ZG6DMkVi4.pt-BR.vtt
2.9 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-BqQbAqok8JU.en.vtt
2.9 kB
Part 11-Module 01-Lesson 16_Tying It All Together/01. Introduction-8tm1144C4T0.ar.vtt
2.9 kB
Part 21-Module 01-Lesson 03_Control Flow/20. L3 08 While Loops V3-7Sf5tcPlKQw.zh-CN.vtt
2.9 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/02. Course Format-rVmwPGFtk_Y.en.vtt
2.9 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/12. Variance Standard Deviation Final Points-vXUgp2375j4.ar.vtt
2.9 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.ar.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/16. Pandas groupby()-w3D0no7E8uw.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.ar.vtt
2.9 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/16. Pandas groupby()-w3D0no7E8uw.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.ja.vtt
2.9 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/06. CSV Format-ra93hy88cok.zh-CN.vtt
2.9 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/24. Drawing Circles-GlIXt29deCA.en-US.vtt
2.9 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. More on Performance Tuning-ZK1FvNH10Ag.pt-BR.vtt
2.9 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/25. Aggregations-ADx1x2ljFB4.pt-BR.vtt
2.9 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/04. Why MongoDB-jjMw4Ju-1CM.pt-BR.vtt
2.9 kB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.pt-BR.vtt
2.9 kB
Part 18-Module 02-Lesson 01_Gathering Data/09. Trees-OVeJU18ADmw.pt-BR.vtt
2.9 kB
Part 18-Module 03-Lesson 01_Assessing Data/14. Programatic Assessment -Bk_Ve3-4eps.en.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/24. Drawing Circles-GlIXt29deCA.en.vtt
2.9 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.ar.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/36. Naive Bayes Strengths and Weaknesses-nfbKTrufPOs.pt-BR.vtt
2.9 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/05. Setting Up Hypotheses - Part II-nByvHz77GiA.pt-BR.vtt
2.9 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/40. Calculated Fields-tR-K9Mvd4B0.pt-BR.vtt
2.9 kB
Part 05-Module 02-Lesson 01_Data and Tables/02. What's a Database - Intro to Relational Databases-V4gbPVdUOpw.en.vtt
2.9 kB
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.pt-BR.vtt
2.9 kB
Part 11-Module 01-Lesson 07_Regressions/34. Comparing Classification and Regression-G_0W912qmGc.en.vtt
2.9 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/06. Accessing Elements of a DataFrame-hZp9cVuiPo0.zh-CN.vtt
2.9 kB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.zh-CN.vtt
2.9 kB
Part 13-Module 01-Lesson 07_Narrative Structures/39. Using extent() for scales-oazLw2JhKiU.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/06. Accessing Elements of a DataFrame-hZp9cVuiPo0.zh-CN.vtt
2.9 kB
Part 11-Module 01-Lesson 09_Clustering/02. Clustering Movies-g8PKffm8IRY.en.vtt
2.9 kB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/16. Type And Quality Plot - Part 1-iRCS1sE78KI.zh-CN.vtt
2.9 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/08. Unit of Analysis vs. Unit of Diversion-rzim0wu_0kM.zh-CN.vtt
2.9 kB
Part 14-Module 01-Lesson 05_Analyzing Results/19. Lessons Learned-5JjCVTc0FGk.pt-BR.vtt
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Part 09-Module 01-Lesson 01_What is EDA/02. Go Exploring-dias-YUpewk.ar.vtt
2.9 kB
Part 11-Module 01-Lesson 04_Decision Trees/34. DT Strengths and Weaknesses-KGnhg76iRfI.en.vtt
2.8 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-gfuknvEP2ro.zh-CN.vtt
2.8 kB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/01. Get an Interview with a Cover Letter!-BH1KY63YfAM.pt-BR.vtt
2.8 kB
Part 21-Module 01-Lesson 05_Scripting/11. Errors And Exceptions-DmthSiy2d0U.en.vtt
2.8 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/09. Questions and Consent-ZmXg42IoG_Q.pt-BR.vtt
2.8 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/06. CSVs in Python-YIDH9HBY3Qk.en.vtt
2.8 kB
Part 18-Module 02-Lesson 01_Gathering Data/08. Scraping Webpages -bAeGbBBAIkE.ar.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-5GYA5j1fqBU.pt-BR.vtt
2.8 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-lVLgiRRhFpQ.ar.vtt
2.8 kB
Part 11-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm-hGKY6BAqJ6o.ar.vtt
2.8 kB
Part 13-Module 01-Lesson 07_Narrative Structures/53. Inspecting Accessor Functions-bRkkMdkkFQw.zh-CN.vtt
2.8 kB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/09. 06 Practice With Marks And Filters-RPAv7WLkutk.en.vtt
2.8 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-lVLgiRRhFpQ.ar.vtt
2.8 kB
Part 11-Module 01-Lesson 03_SVM/10. SVM in SKlearn-R7xQtQzkvTk.en.vtt
2.8 kB
Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-joTa_FeMZ2s.zh-CN.vtt
2.8 kB
Part 13-Module 01-Lesson 04_Design Principles/14. Common and Less Common Charts on plot.ly-V9xxdiwJtWk.ar.vtt
2.8 kB
Part 15-Module 01-Lesson 02_Design Principles/06. Gráficos Comuns e Menos Comuns no plot.ly-V9xxdiwJtWk.ar.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-t_ZSrov187k.ar.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/08. Addressing Missing Data First -ArAGZCUMj9Q.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/34. Comparing Classification and Regression-G_0W912qmGc.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-vsLtePFaOFY.en.vtt
2.8 kB
Part 13-Module 01-Lesson 07_Narrative Structures/18. Author-driven Examples-mr2HGcqk3nU.ar.vtt
2.8 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-vsLtePFaOFY.en.vtt
2.8 kB
Part 11-Module 01-Lesson 16_Tying It All Together/02. Summary-avqZaTECZTQ.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/36. Less is More-urgyRvfWPtU.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/63. Adding Text to the Legend-VPI9MVqGiSM.pt-BR.vtt
2.8 kB
Part 12-Module 01-Lesson 05_Interview Practice/07. Jimmy's Analysis of the Interview-wg535YU4jFw.pt-BR.vtt
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/02. What's Ahead-ggbCydfI1JM.ar.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/20. Broken Requests-QFjKVSmxODY.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/17. Coding It Up-BTFOf2qXy5U.en.vtt
2.8 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/12. Target Population Example-kEFp6xIb8cs.en.vtt
2.8 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -Y288CGrwGy4.zh-CN.vtt
2.8 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/27. What If Our Sample Is Large-WoTCeSTL1eM.zh-CN.vtt
2.8 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/20. Broken Requests-QFjKVSmxODY.en-US.vtt
2.8 kB
Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-f1fz9cLnetM.pt-BR.vtt
2.8 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/20. Broken Requests-QFjKVSmxODY.en.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/21. Order By Part II-XQCjREdOqwE.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data-zQj_waidR5w.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/10. SVM in SKlearn-R7xQtQzkvTk.pt-BR.vtt
2.8 kB
Part 13-Module 01-Lesson 07_Narrative Structures/36. Circles with Bound __data__-JeJ_glcExUs.pt-BR.vtt
2.8 kB
Part 16-Module 03-Lesson 01_Basic SQL/06. Why Do Analysts Like SQL-uCNOtUht2Xc.zh-CN.vtt
2.8 kB
Part 18-Module 02-Lesson 01_Gathering Data/22. Why Do Analysts Like SQL-uCNOtUht2Xc.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/24. Are your Results Just Noise-LjuF5M6ymPA.ar.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/03. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.pt-BR.vtt
2.8 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/04. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-WZRsqdNrC1A.ar.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/31. L2 02 Dictionaries And Identiy Operators V3-QR8HTxCTWi0.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/11. Personal Data Visualization-NtFICAw7tW4.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/20. Object Oriented Design and Charts-2uzNpGWdavc.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/17. Different Types of Narrative Structures-vTlpDo33ezg.zh-CN.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/04. XML in Practice-4xsz7OkDJgM.ar.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-VYwgHHqaUII.pt-BR.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/03. Sampling Distributions Confidence Intervals-gICzUhMVymo.en.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/11. How Do I Find Time for My Nanodegree Program-d-VfUw7wNEQ.ar.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/15. Regularization-l9V5tlIWTvs.zh-CN.vtt
2.8 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/02. Defining Data Visualization-TMH43G11OnQ.zh-CN.vtt
2.8 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-V7zAB9dUaFY.zh-CN.vtt
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/04. Knapsack Problem--xRKazHGtjU.en-US.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/13. Pandas Series-V7zAB9dUaFY.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-AqlvTMZg6HY.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/19. Between 10 and 16-4QIEdzv6g6w.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.zh-CN.vtt
2.8 kB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/04. Knapsack Problem--xRKazHGtjU.en.vtt
2.8 kB
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-ZULplTNbIIs.hi.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/06. Resume Review-L3F2BFGYMtI.en.vtt
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/06. Resume Review-L3F2BFGYMtI.en.vtt
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/06. Resume Review-L3F2BFGYMtI.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-JqyUT7RbvgI.ja.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/08. Addressing Missing Data First -ArAGZCUMj9Q.zh-CN.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/13. Population vs. Cohort-HC2dunMuVW4.zh-CN.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/27. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.zh-CN.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.zh-CN.vtt
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.es-MX.vtt
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Part 11-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.ja.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/23. Drawing Conclusions Example-yAl58ccwyvU.en.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/06. Resume Review-L3F2BFGYMtI.es-MX.vtt
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/06. Resume Review-L3F2BFGYMtI.es-MX.vtt
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/06. Resume Review-L3F2BFGYMtI.es-MX.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/10. Inspect GeoJSON-ThA4r4nzyj4.zh-CN.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/22. Random Observed Values-KFIt2OC3wCI.en.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/27. L2 04 Tuples V3-33xN-AbTMoc.pt-BR.vtt
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Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-PZSPhQCVABg.ja.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data-zQj_waidR5w.ja.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/23. Marks And Filters-FeYRmZHHu0A.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/01. Introduction-0ydaJl3wCkU.ar.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/09. Questions and Consent-ZmXg42IoG_Q.en.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/06. Intro to Sorting-Z6yuIen71zM.zh-CN.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/01. Introduction to Aggregations-5vRf_Ntoxfw.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/08. Calculating Correlation-yLql7kR_6GE.zh-CN.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.ar.vtt
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Part 21-Module 01-Lesson 05_Scripting/21. The Standard Library-Fw3vf0tDrJM.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/08. Calculating Correlation-yLql7kR_6GE.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge-DMhldSg2_vs.pt-BR.vtt
2.8 kB
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-BngCW1fjvFk.hi.vtt
2.8 kB
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.ja.vtt
2.8 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/13. Tracking Down the Remaining Problems-Xblj5rT9i0M.ar.vtt
2.8 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/16. Sizing Overview-sKRWt_iS7zo.zh-CN.vtt
2.8 kB
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.th.vtt
2.8 kB
Part 11-Module 01-Lesson 13_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.zh-CN.vtt
2.8 kB
Part 13-Module 01-Lesson 07_Narrative Structures/36. Circles with Bound __data__-JeJ_glcExUs.en.vtt
2.8 kB
Part 13-Module 01-Lesson 07_Narrative Structures/41. Parsing Data Before the Draw Function-WALbqgiDHNI.zh-CN.vtt
2.8 kB
Part 18-Module 02-Lesson 01_Gathering Data/09. Trees-OVeJU18ADmw.en.vtt
2.8 kB
Part 03-Module 01-Lesson 11_L4 Variability/24. Formula for Avg. Abs. Dev.-ihC1Pm8E8gU.pt-BR.vtt
2.8 kB
Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.ar.vtt
2.8 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/26. Confidence Interval Case Breakdown-gycmvQqw-8s.ar.vtt
2.8 kB
Part 21-Module 01-Lesson 05_Scripting/08. Scripting With Raw Input-Fs9uLV2qfgI.en.vtt
2.8 kB
Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-bR7EoKjN0EM.en.vtt
2.8 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/30. Code Structure and JavaScript-vPCDvEOjP7c.zh-CN.vtt
2.8 kB
Part 21-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.ar.vtt
2.8 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/05. Intro to CSVs-UFiJYYPL95g.zh-CN.vtt
2.8 kB
Part 09-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.ja.vtt
2.8 kB
Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-djTM5fADIVs.ar.vtt
2.8 kB
Part 13-Module 01-Lesson 05_Dimple.js/12. Creating and Drawing the Chart-ZyhYNaRqqL0.en.vtt
2.8 kB
Part 14-Module 01-Lesson 05_Analyzing Results/03. Choosing Invariants-qCnbDgy2yHk.ar.vtt
2.8 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/16. Using A Confidence Interval to Make A Decision-MghT95b6LbQ.pt-BR.vtt
2.8 kB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.zh-CN.vtt
2.8 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/12. Drawing and Altering the Map-soflPyVhb6o.zh-CN.vtt
2.8 kB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/01. Course Introduction-NKBUbUiedzc.zh-CN.vtt
2.8 kB
Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-tfYAGBIR_Ws.en.vtt
2.8 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-8HFOaRdDpek.ar.vtt
2.8 kB
Part 13-Module 01-Lesson 07_Narrative Structures/21. Drone Strikes and Gun Deaths-_MXW29cfh_8.zh-CN.vtt
2.8 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-8HFOaRdDpek.ar.vtt
2.8 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-hmhlyOVAVOs.zh-CN.vtt
2.8 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/37. setInterval and clearInterval-r1sgfqg85us.pt-BR.vtt
2.8 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/29. Formula for Location of Median-lNYLU1b4qoM.zh-CN.vtt
2.8 kB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/01. Get an Interview with a Cover Letter!-BH1KY63YfAM.es-MX.vtt
2.8 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/20. Absolute or Relative Difference-TNcT_v2g3OQ.zh-CN.vtt
2.8 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. Assess Intro -vj3CYBlWj3k.pt-BR.vtt
2.8 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/07. Working In The JavaScript Console-cj4kv_dtqY0.en-US.vtt
2.8 kB
Part 13-Module 01-Lesson 04_Design Principles/54. The Spectrum of Tech in Data Vis-4-tLvLvX9U4.pt-BR.vtt
2.8 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/07. Working In The JavaScript Console-cj4kv_dtqY0.en.vtt
2.8 kB
Part 13-Module 01-Lesson 07_Narrative Structures/61. I am Legend-EdiM9XCqc0Y.zh-CN.vtt
2.8 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/02. Problems Solved by Data Analysts-jZEbCVZzwUk.zh-CN.vtt
2.8 kB
Part 05-Module 01-Lesson 05_Data Quality/07. A Blueprint for Cleaning-3S73cNbhuAk.pt-BR.vtt
2.8 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/48. Matt's Tips for Making Maps-HCYCT2TXhAM.zh-CN.vtt
2.8 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-EwV5Vs2m33w.pt-BR.vtt
2.8 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/19. Pooled Standard Error-iub8yWiO84I.ar.vtt
2.8 kB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.ar.vtt
2.8 kB
Part 05-Module 02-Lesson 01_Data and Tables/10. How Queries Happen-v3EkXogyIL4.zh-CN.vtt
2.8 kB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby-aWc18hHpXRk.ar.vtt
2.8 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/05. Setting Up Hypotheses - Part II-nByvHz77GiA.en.vtt
2.8 kB
Part 17-Module 01-Lesson 16_Logistic Regression/04. Fitting Logistic Regression In Python-baQf-XiZQQ4.zh-CN.vtt
2.8 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-WGD8AWQg9dE.ar.vtt
2.8 kB
Part 05-Module 02-Lesson 05_Deeper into SQL/02. Normalized Design Part One-LQq5F77ANiY.ar.vtt
2.8 kB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.zh-CN.vtt
2.8 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.zh-CN.vtt
2.8 kB
Part 21-Module 01-Lesson 04_Functions/08. Documentation-_Vl9NJkA6JQ.en.vtt
2.8 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.zh-CN.vtt
2.8 kB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.pt-BR.vtt
2.8 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.pt-BR.vtt
2.8 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.zh-CN.vtt
2.8 kB
Part 04-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.en.vtt
2.8 kB
Part 16-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.en.vtt
2.8 kB
Part 17-Module 01-Lesson 11_Confidence Intervals/11. Traditional vs. Bootstrapping Confidence Intervals-eZ8lyiumXDY.zh-CN.vtt
2.8 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/17. Simulating From the Null-sL2yJtHZd8Y.zh-CN.vtt
2.8 kB
Part 21-Module 01-Lesson 03_Control Flow/02. If Statements-jWiIUMrwPqA.en.vtt
2.8 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/07. What is the Standard Deviation Measuring-IbwUJ3ORZ5s.en.vtt
2.8 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/03. Setting Up Hypotheses - Part I-NpZxJg4S6X4.pt-BR.vtt
2.8 kB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/04. Knapsack Problem--xRKazHGtjU.pt-BR.vtt
2.8 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots-GmR3uEM189M.pt-BR.vtt
2.8 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/03. The Benefits of Interactivity-fIIyFYQyGLk.zh-CN.vtt
2.8 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/16. Beginning to Build Our http Requests-ojd7xXOd_64.ar.vtt
2.8 kB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/03. Iterative Parsing-pxUvIP4PQt0.zh-CN.vtt
2.8 kB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/03. Iterative Parsing-pxUvIP4PQt0.zh-CN.vtt
2.8 kB
Part 16-Module 03-Lesson 01_Basic SQL/24. WHERE Statements -mN0uTnlXaxg.pt-BR.vtt
2.8 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge-DMhldSg2_vs.en.vtt
2.8 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/20. Outliers-HKIsvkZUZfo.pt-BR.vtt
2.8 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/37. setInterval and clearInterval-r1sgfqg85us.en-US.vtt
2.8 kB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/12. Final Tips-1ZVBvM54hQw.ar.vtt
2.8 kB
Part 09-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots-llvIDIu3Sw8.ar.vtt
2.8 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-vsLtePFaOFY.pt-BR.vtt
2.8 kB
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.pt-BR.vtt
2.8 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-vsLtePFaOFY.pt-BR.vtt
2.8 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/37. setInterval and clearInterval-r1sgfqg85us.en.vtt
2.8 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/23. Marks And Filters-FeYRmZHHu0A.zh-CN.vtt
2.8 kB
Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-bcwFahJsww0.ar.vtt
2.8 kB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.pt-BR.vtt
2.8 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/03. How This Lesson Is Structured-xfRtO4aFpv0.en.vtt
2.8 kB
Part 06-Module 01-Lesson 03_Analyzing Data/08. Match Operator-FZ8KVv1VOK4.pt-BR.vtt
2.7 kB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/14. What is plot.ly-ZRiAWz-sVlM.en.vtt
2.7 kB
Part 16-Module 03-Lesson 01_Basic SQL/06. Why Businesses Choose Databases-j4ey7--h9r8.pt-BR.vtt
2.7 kB
Part 18-Module 02-Lesson 01_Gathering Data/22. Why Businesses Choose Databases-j4ey7--h9r8.pt-BR.vtt
2.7 kB
Part 18-Module 03-Lesson 01_Assessing Data/14. Programatic Assessment -Bk_Ve3-4eps.pt-BR.vtt
2.7 kB
Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.ar.vtt
2.7 kB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/17. 07 Calculated Fields-dXEvq03E5lc.en.vtt
2.7 kB
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-HEnJRwJ23us.zh-CN.vtt
2.7 kB
Part 21-Module 01-Lesson 04_Functions/11. L4 08 Lambda Expressions V3-wkEmPz1peJM.pt-BR.vtt
2.7 kB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/17. 07 Calculated Fields-dXEvq03E5lc.pt-BR.vtt
2.7 kB
Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment Solution-LhdGQC_vjEs.pt-BR.vtt
2.7 kB
Part 03-Module 01-Lesson 11_L4 Variability/24. Formula for Avg. Abs. Dev.-ihC1Pm8E8gU.en.vtt
2.7 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/04. Why MongoDB-jjMw4Ju-1CM.en.vtt
2.7 kB
Part 12-Module 02-Lesson 06_Graphs/03. Directions and Cycles-lF0vUktQDPo.en-US.vtt
2.7 kB
Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.es-ES.vtt
2.7 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/23. McDonald's-29Vf6PytVbA.zh-CN.vtt
2.7 kB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/23. McDonald's-29Vf6PytVbA.zh-CN.vtt
2.7 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-iJEBxsKDDoE.zh-CN.vtt
2.7 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps-zSSNWZuVG8Y.en.vtt
2.7 kB
Part 11-Module 01-Lesson 12_Feature Selection/02. A New Enron Feature-m2-LkgEfLO0.ar.vtt
2.7 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. More on Performance Tuning-ZK1FvNH10Ag.zh-CN.vtt
2.7 kB
Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-DxCwtkrYR-s.zh-CN.vtt
2.7 kB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/01. t-Distribution-N6wKbV1DVos.zh-CN.vtt
2.7 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/20. Building the Linear Model-zyIc0sXYk2A.ar.vtt
2.7 kB
Part 12-Module 02-Lesson 06_Graphs/03. Directions and Cycles-lF0vUktQDPo.en.vtt
2.7 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/16. Performance Tuning 2-arMtEhSoq7E.ar.vtt
2.7 kB
Part 17-Module 01-Lesson 16_Logistic Regression/07. Interpreting Results in Python-IY88UTiJltQ.pt-BR.vtt
2.7 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/39. Update the Title-ut83yNUYLmc.ar.vtt
2.7 kB
Part 11-Module 01-Lesson 09_Clustering/01. Unsupervised Learning-Mx9f99bRB3Q.zh-CN.vtt
2.7 kB
Part 21-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.en.vtt
2.7 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data-zQj_waidR5w.en.vtt
2.7 kB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.ja.vtt
2.7 kB
Part 18-Module 02-Lesson 01_Gathering Data/01. Introduction-XtJN72lBo94.ar.vtt
2.7 kB
Part 05-Module 01-Lesson 05_Data Quality/19. More About Correcting Data-vWBMgSQvsVk.zh-CN.vtt
2.7 kB
Part 13-Module 01-Lesson 05_Dimple.js/31. Customizing a Dimple Chart-93MgOnKP5m0.en.vtt
2.7 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/29. Why D3-2qZ3d2WOvwE.pt-BR.vtt
2.7 kB
Part 03-Module 01-Lesson 20_L8 Estimation/06. Interval Estimate for Population Mean-ECRw3cSiy6o.zh-CN.vtt
2.7 kB
Part 11-Module 01-Lesson 02_Naive Bayes/36. Naive Bayes Strengths and Weaknesses-nfbKTrufPOs.zh-CN.vtt
2.7 kB
Part 16-Module 03-Lesson 01_Basic SQL/34. LIKE Operator-O5z6eWkNip4.ar.vtt
2.7 kB
Part 13-Module 01-Lesson 04_Design Principles/47. Discovery versus Presentation-znQ3iBhhJtA.pt-BR.vtt
2.7 kB
Part 09-Module 01-Lesson 02_R Basics/12. Factor Variables-0bkvt4KEqjE.zh-CN.vtt
2.7 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.pt-BR.vtt
2.7 kB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.pt-BR.vtt
2.7 kB
Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-f1fz9cLnetM.en.vtt
2.7 kB
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-t2Nq3MFK_pg.ar.vtt
2.7 kB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/02. Cleaning with String Functions-y1fduSu7Ovc.zh-CN.vtt
2.7 kB
Part 12-Module 02-Lesson 05_Trees/19. Red-Black Trees - Insertion-dIuWLtWnkgs.pt-BR.vtt
2.7 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/07. Packages Overview-sCQoQsmI3F0.pt-BR.vtt
2.7 kB
Part 11-Module 01-Lesson 12_Feature Selection/16. Lasso Regression-qU1_cj4LfLY.pt-BR.vtt
2.7 kB
Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.en.vtt
2.7 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/29. Data Analysis and Related Terms-9g9_tlhbNSw.en.vtt
2.7 kB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/07. DF - Sample SD-Jfk3egev9UM.en.vtt
2.7 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/26. Predicting Based on Many Features-oZqGlJbRZu4.en.vtt
2.7 kB
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-S-pjRUJAGTs.pt-BR.vtt
2.7 kB
Part 12-Module 02-Lesson 06_Graphs/03. Directions and Cycles-lF0vUktQDPo.pt-BR.vtt
2.7 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge-DMhldSg2_vs.ja.vtt
2.7 kB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/05. Cleaning With More Advanced String Functions-E6cK8RbYGEc.pt-BR.vtt
2.7 kB
Part 12-Module 01-Lesson 01_Ace Your Interview/02. Interviewing Conversations-klqXp09Pen4.en.vtt
2.7 kB
Part 07-Module 01-Lesson 01_GitHub Review/02. GitHub profile important items-prvPVTjVkwQ.zh-CN.vtt
2.7 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.ar.vtt
2.7 kB
Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-VYwgHHqaUII.en.vtt
2.7 kB
Part 12-Module 02-Lesson 05_Trees/12. BSTs-abRNGLhGUmE.en-US.vtt
2.7 kB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/02. Multiple Linear Regression-rvYZp99nj6c.en.vtt
2.7 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/15. Using mongoimport-JVYH9B6Obpg.pt-BR.vtt
2.7 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-Hs3__UsSyL8.en.vtt
2.7 kB
Part 13-Module 01-Lesson 07_Narrative Structures/11. Personal Data Visualization-NtFICAw7tW4.pt-BR.vtt
2.7 kB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/15. SD of Karma Points per Post-uCRzrlaA8mg.en.vtt
2.7 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax-7XyFjPDPoZQ.zh-CN.vtt
2.7 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-VUfaXWrr3oY.ar.vtt
2.7 kB
Part 12-Module 02-Lesson 05_Trees/12. BSTs-abRNGLhGUmE.en.vtt
2.7 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/02. Lesson Overview-1EzlGH4Biu0.pt-BR.vtt
2.7 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/06. Connecting To Data-WmsAtqbwRI0.pt-BR.vtt
2.7 kB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Window Functions-gp0RPgkDHsQ.en.vtt
2.7 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/16. Using A Confidence Interval to Make A Decision-MghT95b6LbQ.en.vtt
2.7 kB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/04. Writing Your Introduction-5S5PH73WLLY.en.vtt
2.7 kB
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-AaLIKufl_mY.en.vtt
2.7 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-Mta8Hv36k7Q.en.vtt
2.7 kB
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.zh-CN.vtt
2.7 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-Mta8Hv36k7Q.en.vtt
2.7 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/03. Facebook Experiment-VqLX0wnrldc.pt-BR.vtt
2.7 kB
Part 13-Module 01-Lesson 07_Narrative Structures/27. Defining a Join-Xo-OJXzS0tQ.en.vtt
2.7 kB
Part 04-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.zh-CN.vtt
2.7 kB
Part 16-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.zh-CN.vtt
2.7 kB
Part 09-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.pt-BR.vtt
2.7 kB
Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-IMWsjjIeOrY.ar.vtt
2.7 kB
Part 11-Module 01-Lesson 07_Regressions/20. Extracting Score Data from sklearn-NhD4oUuhvO8.pt-BR.vtt
2.7 kB
Part 18-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty Messy -WG6mil60jq0.zh-CN.vtt
2.7 kB
Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.ja.vtt
2.7 kB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/04. Ways in the Open Street Map XML-1OwIbj9dcLo.zh-CN.vtt
2.7 kB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/05. Ways in the Open Street Map XML-1OwIbj9dcLo.zh-CN.vtt
2.7 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.ar.vtt
2.7 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1 Solution -I1enB5CA85Q.en.vtt
2.7 kB
Part 06-Module 01-Lesson 03_Analyzing Data/08. Match Operator-FZ8KVv1VOK4.en.vtt
2.7 kB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/04. Writing Your Introduction-5S5PH73WLLY.pt-BR.vtt
2.7 kB
Part 21-Module 01-Lesson 03_Control Flow/07. Truth Value Testing-e52uw7ejV8k.ar.vtt
2.7 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-Mta8Hv36k7Q.pt-BR.vtt
2.7 kB
Part 13-Module 01-Lesson 05_Dimple.js/17. Inspecting the X-axis-huZPg2gRmLk.ar.vtt
2.7 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/20. Outliers-HKIsvkZUZfo.en.vtt
2.7 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-Mta8Hv36k7Q.pt-BR.vtt
2.7 kB
Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-SwbreslrpqQ.pt-BR.vtt
2.7 kB
Part 18-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python-KS6cKoKe8ms.ar.vtt
2.7 kB
Part 11-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary-gBwGPI0srBE.zh-CN.vtt
2.7 kB
Part 17-Module 01-Lesson 16_Logistic Regression/07. Interpreting Results in Python-IY88UTiJltQ.en.vtt
2.7 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/19. Using Beautiful Soup-_rDjie-TaS8.zh-CN.vtt
2.7 kB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/04. Writing Your Introduction-5S5PH73WLLY.es-MX.vtt
2.7 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/22. Decomposing Visualizations-iJ8t2FsPW4c.ar.vtt
2.7 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/10. -v5CqqhgvG-U.zh-CN.vtt
2.7 kB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Running Totals And Count-rNJwmnzUTxg.en.vtt
2.7 kB
Part 21-Module 01-Lesson 03_Control Flow/28. Zip and Enumerate-bSJPzVArE7M.pt-BR.vtt
2.7 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/06. Critical Regions-UF3japjNx98.en.vtt
2.7 kB
Part 16-Module 03-Lesson 02_SQL Joins/13. Motivation for Other JOINs-3qdv1Ojc9Og.ar.vtt
2.7 kB
Part 18-Module 03-Lesson 01_Assessing Data/06. Types vs. Steps -oZmndg-BnPk.zh-CN.vtt
2.7 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.pt-BR.vtt
2.7 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/08. Whitespace-UxkIwcOczQQ.zh-CN.vtt
2.7 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/40. Calculated Fields-tR-K9Mvd4B0.en.vtt
2.7 kB
Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results-ZFn9xVQ0hD4.pt-BR.vtt
2.7 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/01. Welcome!-KJT4Z0xpHns.ar.vtt
2.7 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-P8ZxaAQTZXQ.ar.vtt
2.7 kB
Part 17-Module 01-Lesson 14_Regression/13. Fitting A Regression Line-xQob80zrT3s.zh-CN.vtt
2.7 kB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/02. Multiple Linear Regression-rvYZp99nj6c.pt-BR.vtt
2.7 kB
Part 11-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-oZkDSuhBEkE.ar.vtt
2.7 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/06. Words of Wisdom from Zipfian Academy-ani9_ZalK-8.pt-BR.vtt
2.7 kB
Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-PZSPhQCVABg.zh-CN.vtt
2.7 kB
Part 17-Module 01-Lesson 14_Regression/02. Introduction to Machine Learning-pLcFPPI1L-0.pt-BR.vtt
2.7 kB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/15. What About More Than Two Variables -ufKcdUbLj9c.zh-CN.vtt
2.7 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/15. Hypotheses-DepOzUJw_bQ.zh-CN.vtt
2.7 kB
Part 11-Module 01-Lesson 07_Regressions/17. Coding It Up-BTFOf2qXy5U.pt-BR.vtt
2.7 kB
Part 17-Module 01-Lesson 14_Regression/16. How Do We Interpret Results-eLk0XGGMaCE.en.vtt
2.7 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/06. Critical Regions-UF3japjNx98.pt-BR.vtt
2.7 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Data Types-gT6EYlsLZkE.ar.vtt
2.7 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/03. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.en.vtt
2.7 kB
Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-CvTXyvw7QLc.ar.vtt
2.7 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/21. Variability-1KmFcGt6Uo0.zh-CN.vtt
2.7 kB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/04. Gathering Data-r7BHGq_0P9Q.ar.vtt
2.7 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/04. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.en.vtt
2.7 kB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/01. Get an Interview with a Cover Letter!-BH1KY63YfAM.zh-CN.vtt
2.7 kB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML and Trees-766JMEtZCPE.pt-BR.vtt
2.7 kB
Part 19-Module 01-Lesson 02_Design/16. General Design Tips-Zq-wMwOfQqY.pt-BR.vtt
2.7 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/21. One tailed or two tailed-Cf8PvkUR1NQ.en.vtt
2.7 kB
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-GuBics_6HOk.ja.vtt
2.7 kB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Running Totals And Count-rNJwmnzUTxg.pt-BR.vtt
2.7 kB
Part 07-Module 01-Lesson 01_GitHub Review/06. Quick Fixes-Lb9e2KemR6I.ar.vtt
2.7 kB
Part 09-Module 01-Lesson 01_What is EDA/05. Goals of EDA-NEvuulahg2g.zh-CN.vtt
2.7 kB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/17. 07 Calculated Fields-dXEvq03E5lc.zh-CN.vtt
2.7 kB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/22. Bootstrapping-42j3YclcZ4Q.ar.vtt
2.7 kB
Part 13-Module 01-Lesson 05_Dimple.js/34. Summary of Dimple and Chart Types-OrdADko3k1Q.zh-CN.vtt
2.7 kB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.ar.vtt
2.7 kB
Part 11-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data-x2dmBUEKQIA.en.vtt
2.7 kB
Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-OurfO1ZR2GU.zh-CN.vtt
2.7 kB
Part 11-Module 01-Lesson 07_Regressions/20. Extracting Score Data from sklearn-NhD4oUuhvO8.en.vtt
2.7 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/21. Rankings of Visual Encodings-ycsXqX7T80Y.ar.vtt
2.7 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/17. -zDs_pN7G-wQ.en-US.vtt
2.7 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/06. Ethical Considerations for Diversion-Zf0XzYNsado.ar.vtt
2.7 kB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/08. Rankings of Visual Encodings - Data Visualization and D3.js-ycsXqX7T80Y.ar.vtt
2.7 kB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/18. 39. SAD-tya_avP-hKc.pt-BR.vtt
2.7 kB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.ar.vtt
2.7 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/17. -zDs_pN7G-wQ.en.vtt
2.7 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-UkGwgerJU44.pt-BR.vtt
2.7 kB
Part 21-Module 01-Lesson 05_Scripting/11. Errors And Exceptions-DmthSiy2d0U.zh-CN.vtt
2.7 kB
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-hxxa0KAkB1o.ar.vtt
2.7 kB
Part 17-Module 01-Lesson 11_Confidence Intervals/08. Statistical vs. Practical Differences-RKHD1wzxxPA.zh-CN.vtt
2.7 kB
Part 17-Module 01-Lesson 16_Logistic Regression/02. Fitting Logistic Regression-Dg0rBDQnIYg.en.vtt
2.7 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/29. L2 03 Sets V2-eIHNFgTFfnA.pt-BR.vtt
2.7 kB
Part 13-Module 01-Lesson 07_Narrative Structures/03. Correlation vs Causation-8u96-UEf_ms.zh-CN.vtt
2.7 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/23. Keeping Trust and Drawing Circles-pBLeU5bbKak.en-US.vtt
2.7 kB
Part 14-Module 01-Lesson 05_Analyzing Results/08. Single Metric Introduction-StP9L9f70EU.zh-CN.vtt
2.7 kB
Part 12-Module 01-Lesson 01_Ace Your Interview/02. Interviewing Conversations-klqXp09Pen4.es-MX.vtt
2.7 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/35. Summary of the Update Function-IVmBlMgErzY.ar.vtt
2.7 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/23. Keeping Trust and Drawing Circles-pBLeU5bbKak.en.vtt
2.7 kB
Part 18-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty Messy -WG6mil60jq0.en.vtt
2.7 kB
Part 11-Module 01-Lesson 09_Clustering/11. K-Means Clustering Visualization 3-WfwX3B4d8_I.en.vtt
2.7 kB
Part 13-Module 01-Lesson 07_Narrative Structures/30. Thinking with Venn Diagrams-C1aHeMSeIdk.ar.vtt
2.7 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-JqyUT7RbvgI.zh-CN.vtt
2.6 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/19. Sizing Triggering-ae9SWJxGM0w.zh-CN.vtt
2.6 kB
Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.ar.vtt
2.6 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/01. What is Data Visualization-mfLklbVU7r0.pt-BR.vtt
2.6 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/29. Let's Make a Bar Chart-PlhGAjAZFhw.ar.vtt
2.6 kB
Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.en.vtt
2.6 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/09. Types Of Errors - Part II-mbdSQ5CjdFs.zh-CN.vtt
2.6 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-6CiZB0N7y64.zh-CN.vtt
2.6 kB
Part 12-Module 02-Lesson 05_Trees/05. Tree Traversal-KZOdmzypynw.en-US.vtt
2.6 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/02. Unit of Diversion Overview-Gh32VbXrmdQ.zh-CN.vtt
2.6 kB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.pt-BR.vtt
2.6 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-6CiZB0N7y64.zh-CN.vtt
2.6 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/31. What Do You Get with a Good Klout Score-7N7MBPJKCfw.en-US.vtt
2.6 kB
Part 17-Module 01-Lesson 13_Case Study AB tests/02. AB Testing-EcWvhbIjT9o.zh-CN.vtt
2.6 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/24. MM CLT-DqC-pgcEam4.zh-CN.vtt
2.6 kB
Part 13-Module 01-Lesson 04_Design Principles/25. Communicating with Color-QnFtYKXf7TQ.zh-CN.vtt
2.6 kB
Part 15-Module 01-Lesson 02_Design Principles/13. Communicating with Color-QnFtYKXf7TQ.zh-CN.vtt
2.6 kB
Part 12-Module 02-Lesson 05_Trees/05. Tree Traversal-KZOdmzypynw.en.vtt
2.6 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-Hs3__UsSyL8.pt-BR.vtt
2.6 kB
Part 13-Module 01-Lesson 04_Design Principles/54. The Spectrum of Tech in Data Vis-4-tLvLvX9U4.en.vtt
2.6 kB
Part 16-Module 03-Lesson 02_SQL Joins/02. Why Use Separate Tables-UIQBtpmqYOs.zh-CN.vtt
2.6 kB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components-AiFcaHRGdEA.pt-BR.vtt
2.6 kB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components-AiFcaHRGdEA.pt-BR.vtt
2.6 kB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components-AiFcaHRGdEA.pt-BR.vtt
2.6 kB
Part 19-Module 01-Lesson 02_Design/19. Same Data Different Stories-jSSnkz3QT5Y.ar.vtt
2.6 kB
Part 16-Module 03-Lesson 01_Basic SQL/18. ORDER BY Statement-wqj2As31LqI.ar.vtt
2.6 kB
Part 17-Module 01-Lesson 13_Case Study AB tests/11. Metric - Average Reading Duration-w6Y9ZxHDEbw.en.vtt
2.6 kB
Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment Solution-LhdGQC_vjEs.zh-CN.vtt
2.6 kB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/08. Hierarchies with Trina-ys8Cn0o5gNI.ar.vtt
2.6 kB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/03. Hierarchies with Trina-ys8Cn0o5gNI.ar.vtt
2.6 kB
Part 12-Module 02-Lesson 05_Trees/19. Red-Black Trees - Insertion-dIuWLtWnkgs.zh-CN.vtt
2.6 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-WnQoZzxas-g.pt-BR.vtt
2.6 kB
Part 17-Module 01-Lesson 13_Case Study AB tests/05. Experiment I-JLKAdT2JESk.en.vtt
2.6 kB
Part 03-Module 01-Lesson 13_L5 Standardizing/17. Z-Score-pftNHu4uevA.pt-BR.vtt
2.6 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-K6zJtrTEf6k.zh-CN.vtt
2.6 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/06. Words of Wisdom from Zipfian Academy-ani9_ZalK-8.en.vtt
2.6 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/15. Using mongoimport-JVYH9B6Obpg.en.vtt
2.6 kB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/05. Investigation Process-5o2x4UsumLY.pt-BR.vtt
2.6 kB
Part 13-Module 01-Lesson 07_Narrative Structures/39. Using extent() for scales-oazLw2JhKiU.zh-CN.vtt
2.6 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/14. Common Types of Hypothesis Tests-8hv8KnvQ6JY.en.vtt
2.6 kB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/15. Different Bin Sizes-_wOXWBZkL58.pt-BR.vtt
2.6 kB
Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-pn3MunHovMc.ar.vtt
2.6 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-dtnjREsGfXI.zh-CN.vtt
2.6 kB
Part 12-Module 01-Lesson 01_Ace Your Interview/02. Interviewing Conversations-klqXp09Pen4.pt-BR.vtt
2.6 kB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/11. CAST-LbyOq4ofLng.zh-CN.vtt
2.6 kB
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.zh-CN.vtt
2.6 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts-zbjRiYSSR_Y.zh-CN.vtt
2.6 kB
Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-wl3gjMMrYwM.ar.vtt
2.6 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-Z4n3jR-FZP8.pt-BR.vtt
2.6 kB
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-GuBics_6HOk.pt-BR.vtt
2.6 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/13. Binomial Distribution-PVTChqpnr5Q.zh-CN.vtt
2.6 kB
Part 17-Module 01-Lesson 11_Confidence Intervals/03. Sampling Distributions Confidence Intervals-gICzUhMVymo.pt-BR.vtt
2.6 kB
Part 07-Module 01-Lesson 01_GitHub Review/03. Good GitHub repository-qBi8Q1EJdfQ.ar.vtt
2.6 kB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/18. 08 Table Calculations-Vkf3Ft93zMc.zh-CN.vtt
2.6 kB
Part 16-Module 03-Lesson 02_SQL Joins/03. Your First JOIN-HkX9fkNRbU8.ar.vtt
2.6 kB
Part 21-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.zh-CN.vtt
2.6 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Calculating the Mean-1nzZxmJ8xvU.pt-BR.vtt
2.6 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/31. What Do You Get with a Good Klout Score-7N7MBPJKCfw.en.vtt
2.6 kB
Part 12-Module 02-Lesson 06_Graphs/06. Graph Representations-uw9u6dtl0WA.pt-BR.vtt
2.6 kB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/03. Your First Subquery-cTM1jPYXLoQ.zh-CN.vtt
2.6 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.ja.vtt
2.6 kB
Part 16-Module 03-Lesson 01_Basic SQL/15. LIMIT Statement-cCPHNNhBgpQ.ar.vtt
2.6 kB
Part 17-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.th.vtt
2.6 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/17. Collecting Stadium Locations-CqE3Zqv21Wo.pt-BR.vtt
2.6 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Introduction to Summary Statistics-PCZmHCrcMcw.pt-BR.vtt
2.6 kB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-cgWAzXtglF0.pt-BR.vtt
2.6 kB
Part 11-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.ja.vtt
2.6 kB
Part 12-Module 01-Lesson 01_Ace Your Interview/02. Interviewing Conversations-klqXp09Pen4.zh-CN.vtt
2.6 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/01. Introduction to Course-gR_buSP6sdw.zh-CN.vtt
2.6 kB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/28. Assumptions-CdoWdNAKSYw.en.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/01. Introduction -rkRn1Nh-6lg.ar.vtt
2.6 kB
Part 05-Module 02-Lesson 01_Data and Tables/02. What's a Database - Intro to Relational Databases-V4gbPVdUOpw.zh-CN.vtt
2.6 kB
Part 17-Module 01-Lesson 14_Regression/10. What Defines A Line-lTqwhsSNP2c.en.vtt
2.6 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/20. Broken Requests-QFjKVSmxODY.zh-CN.vtt
2.6 kB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.en.vtt
2.6 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-2DwKMiFjGPE.ar.vtt
2.6 kB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Aggregates in Window Functions-Dxew5w3VF7k.en.vtt
2.6 kB
Part 11-Module 01-Lesson 09_Clustering/11. K-Means Clustering Visualization 3-WfwX3B4d8_I.pt-BR.vtt
2.6 kB
Part 11-Module 01-Lesson 10_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.zh-CN.vtt
2.6 kB
Part 12-Module 02-Lesson 06_Graphs/06. Graph Representations-uw9u6dtl0WA.en-US.vtt
2.6 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-a6oG3g7aKR4.ar.vtt
2.6 kB
Part 05-Module 02-Lesson 03_Elements of SQL/10. Why Do It in the Database-6vfZYhhmuLU.pt-BR.vtt
2.6 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-a6oG3g7aKR4.ar.vtt
2.6 kB
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.en.vtt
2.6 kB
Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.ar.vtt
2.6 kB
Part 12-Module 02-Lesson 06_Graphs/06. Graph Representations-uw9u6dtl0WA.en.vtt
2.6 kB
Part 21-Module 01-Lesson 03_Control Flow/28. Zip and Enumerate-bSJPzVArE7M.en.vtt
2.6 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-8oM8KjsntG8.ar.vtt
2.6 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/01. Instructor Introduction Juno Lee-to8Pp3PCOZo.ar.vtt
2.6 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/12. Types Of Errors - Part III-Z-srkCPsdaM.zh-CN.vtt
2.6 kB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/23. Interpreting Interactions-XV6S2srsdxw.zh-CN.vtt
2.6 kB
Part 21-Module 01-Lesson 05_Scripting/05. Running A Python Script-vMKemwCderg.pt-BR.vtt
2.6 kB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components-AiFcaHRGdEA.es-MX.vtt
2.6 kB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components-AiFcaHRGdEA.es-MX.vtt
2.6 kB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components-AiFcaHRGdEA.es-MX.vtt
2.6 kB
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.zh-CN.vtt
2.6 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/10. Estimating Click-Through-Probability-Hkbc_vcb7D8.pt-BR.vtt
2.6 kB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby-aWc18hHpXRk.pt-BR.vtt
2.6 kB
Part 11-Module 01-Lesson 07_Regressions/32. Visualizing Regression-zQAHZhcsXoQ.ar.vtt
2.6 kB
Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-eAKVYAR_VlY.pt-BR.vtt
2.6 kB
Part 16-Module 03-Lesson 03_SQL Aggregations/01. Introduction to Aggregations-5vRf_Ntoxfw.en.vtt
2.6 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-plnMY4iATyU.ar.vtt
2.6 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/21. One tailed or two tailed-Cf8PvkUR1NQ.pt-BR.vtt
2.6 kB
Part 11-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter-m2a2K4lprQw.zh-CN.vtt
2.6 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1-J4X9r0EGH3k.en.vtt
2.6 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/01. Introduction-yod62-mxXR4.zh-CN.vtt
2.6 kB
Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.pt-BR.vtt
2.6 kB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components-AiFcaHRGdEA.en.vtt
2.6 kB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components-AiFcaHRGdEA.en.vtt
2.6 kB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components-AiFcaHRGdEA.en.vtt
2.6 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/22. Variability Example-kTXI_wnTbVk.ar.vtt
2.6 kB
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-GuBics_6HOk.en.vtt
2.6 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots-GmR3uEM189M.en.vtt
2.6 kB
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-S-pjRUJAGTs.en.vtt
2.6 kB
Part 18-Module 03-Lesson 01_Assessing Data/01. Introduction-4U3nFMf2KEs.ar.vtt
2.6 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/34. From Source Code to Graphic-PIqgFTee-lk.pt-BR.vtt
2.6 kB
Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.pt-BR.vtt
2.6 kB
Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-NvgWKf-iBsw.pt-BR.vtt
2.6 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-QJxhBCWK6BQ.ar.vtt
2.6 kB
Part 11-Module 01-Lesson 09_Clustering/02. Clustering Movies-g8PKffm8IRY.zh-CN.vtt
2.6 kB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML and Trees-766JMEtZCPE.en.vtt
2.6 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/02. Hypothesis Testing-9GbHHpiK6wk.en.vtt
2.6 kB
Part 12-Module 02-Lesson 05_Trees/03. Tree Terminology-mPUsDUR_sj8.en-US.vtt
2.6 kB
Part 13-Module 01-Lesson 04_Design Principles/03. Parts of Speech Analogy for Data Vis-bO8clma7Mnc.ar.vtt
2.6 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/07. Packages Overview-sCQoQsmI3F0.en.vtt
2.6 kB
Part 12-Module 02-Lesson 05_Trees/03. Tree Terminology-mPUsDUR_sj8.en.vtt
2.6 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/22. Simulation Applet-yu4mdXybrts.zh-CN.vtt
2.6 kB
Part 09-Module 01-Lesson 01_What is EDA/04. Aude's Interest in Data-DDNSMG_RltY.ar.vtt
2.6 kB
Part 12-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question-XvvKBmKC_84.en-US.vtt
2.6 kB
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.ar.vtt
2.6 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-FpcCdcKFBKM.ar.vtt
2.6 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/06. Connecting To Data-WmsAtqbwRI0.en.vtt
2.6 kB
Part 14-Module 01-Lesson 05_Analyzing Results/02. Sanity Checks-OVnlC_T3EpI.zh-CN.vtt
2.6 kB
Part 12-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question-XvvKBmKC_84.en.vtt
2.6 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/25. Aggregations-ADx1x2ljFB4.zh-CN.vtt
2.6 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 1-V7STsHoZ2gA.ar.vtt
2.6 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/23. MMs-nCwZE4n4FAs.en.vtt
2.6 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.pt-BR.vtt
2.6 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-BqQbAqok8JU.zh-CN.vtt
2.6 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-BqQbAqok8JU.zh-CN.vtt
2.6 kB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.en.vtt
2.6 kB
Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-SwbreslrpqQ.en.vtt
2.6 kB
Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-NjuenhkC-44.zh-CN.vtt
2.6 kB
Part 13-Module 01-Lesson 05_Dimple.js/11. Chart Layout and Group Tags--2yj49s7v5w.ar.vtt
2.6 kB
Part 18-Module 02-Lesson 01_Gathering Data/09. Trees-OVeJU18ADmw.zh-CN.vtt
2.6 kB
Part 12-Module 02-Lesson 08_Technical Interview - Python/01. Interview Introduction-dRsHYt1Lddc.en-US.vtt
2.6 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/13. Thematic Maps-Jw2q-B2kM9k.pt-BR.vtt
2.6 kB
Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-f1fz9cLnetM.zh-CN.vtt
2.6 kB
Part 16-Module 03-Lesson 01_Basic SQL/21. Order By Part II-XQCjREdOqwE.pt-BR.vtt
2.6 kB
Part 16-Module 03-Lesson 01_Basic SQL/43. AND BETWEEN Operators-nBuDPneWcKY.pt-BR.vtt
2.6 kB
Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results-ZFn9xVQ0hD4.en.vtt
2.6 kB
Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-bR7EoKjN0EM.zh-CN.vtt
2.6 kB
Part 12-Module 02-Lesson 08_Technical Interview - Python/01. Interview Introduction-dRsHYt1Lddc.en.vtt
2.6 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/43. Table Calculations-VJfCNO0J9jY.pt-BR.vtt
2.6 kB
Part 21-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.zh-CN.vtt
2.6 kB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.en-US.vtt
2.6 kB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-IwcoGtFuYSo.pt-BR.vtt
2.6 kB
Part 12-Module 02-Lesson 05_Trees/12. BSTs-abRNGLhGUmE.pt-BR.vtt
2.6 kB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/18. 08 Table Calculations-Vkf3Ft93zMc.en.vtt
2.6 kB
Part 03-Module 01-Lesson 20_L8 Estimation/01. Summary-51hx5u2EMZA.en.vtt
2.6 kB
Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.pt-BR.vtt
2.6 kB
Part 13-Module 01-Lesson 04_Design Principles/47. Discovery versus Presentation-znQ3iBhhJtA.en.vtt
2.6 kB
Part 16-Module 03-Lesson 01_Basic SQL/30. Arithmetic Operators-fgcJdiNECxI.ar.vtt
2.6 kB
Part 16-Module 03-Lesson 03_SQL Aggregations/05. COUNT NULLs-ngxgqfFFFLQ.ar.vtt
2.6 kB
Part 17-Module 01-Lesson 14_Regression/06. Scatter Plots -DvlxZ37O4i8.pt-BR.vtt
2.6 kB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/09. Scatter Plots -DvlxZ37O4i8.pt-BR.vtt
2.6 kB
Part 11-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye-sJgPnuiHrs8.en.vtt
2.6 kB
Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-NvgWKf-iBsw.en.vtt
2.6 kB
Part 12-Module 02-Lesson 05_Trees/05. Tree Traversal-KZOdmzypynw.pt-BR.vtt
2.6 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/10. Estimating Click-Through-Probability-Hkbc_vcb7D8.en.vtt
2.6 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/28. Improving Plots and Sharing Findings-anglRHbmsfw.pt-BR.vtt
2.5 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-zlopUR9utUY.ar.vtt
2.5 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-zlopUR9utUY.ar.vtt
2.5 kB
Part 05-Module 01-Lesson 05_Data Quality/05. Measuring Data Quality-dj46LqDBFYM.en.vtt
2.5 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/19. Checking the Nest Return-hCXhsYVLqig.en.vtt
2.5 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/19. Checking the Nest Return-hCXhsYVLqig.pt-BR.vtt
2.5 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/02. Course Format-rVmwPGFtk_Y.zh-CN.vtt
2.5 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/23. Drawing Conclusions Example-yAl58ccwyvU.zh-CN.vtt
2.5 kB
Part 21-Module 01-Lesson 05_Scripting/08. Scripting With Raw Input-Fs9uLV2qfgI.zh-CN.vtt
2.5 kB
Part 12-Module 02-Lesson 05_Trees/17. Heap Implementation-2LAdml6_pDY.en-US.vtt
2.5 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/14. Anscombe’s Quartet-Ftp3mmItV-k.ar.vtt
2.5 kB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Anscombe’s Quartet-Ftp3mmItV-k.ar.vtt
2.5 kB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/15. Finches-ONhDQKYCJlE.en.vtt
2.5 kB
Part 08-Module 01-Lesson 01_Conduct a Job Search/02. Job Search Mindset-cBk7bno3KS0.pt-BR.vtt
2.5 kB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/08. Time When You Dealt With Failure-Qb4o_4hCuyg.en.vtt
2.5 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-Z4n3jR-FZP8.en.vtt
2.5 kB
Part 12-Module 02-Lesson 05_Trees/17. Heap Implementation-2LAdml6_pDY.en.vtt
2.5 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-q46nO0mznXM.ar.vtt
2.5 kB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Statement-DRmkKVhe6-s.ar.vtt
2.5 kB
Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.en.vtt
2.5 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-EwV5Vs2m33w.en.vtt
2.5 kB
Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.ar.vtt
2.5 kB
Part 17-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.ar.vtt
2.5 kB
Part 11-Module 01-Lesson 07_Regressions/17. Coding It Up-BTFOf2qXy5U.zh-CN.vtt
2.5 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.en.vtt
2.5 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.en.vtt
2.5 kB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/05. Investigation Process-5o2x4UsumLY.en.vtt
2.5 kB
Part 11-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye-sJgPnuiHrs8.pt-BR.vtt
2.5 kB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/03. 01 Connecting To Data-zuJPPSlbW2c.en.vtt
2.5 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-UkGwgerJU44.en.vtt
2.5 kB
Part 12-Module 01-Lesson 05_Interview Practice/07. Jimmy's Analysis of the Interview-wg535YU4jFw.zh-CN.vtt
2.5 kB
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-AaLIKufl_mY.zh-CN.vtt
2.5 kB
Part 13-Module 01-Lesson 05_Dimple.js/31. Customizing a Dimple Chart-93MgOnKP5m0.zh-CN.vtt
2.5 kB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Window Functions-gp0RPgkDHsQ.pt-BR.vtt
2.5 kB
Part 12-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-R9AtVBq2Z5E.en.vtt
2.5 kB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.ar.vtt
2.5 kB
Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files-w-ZG6DMkVi4.en.vtt
2.5 kB
Part 05-Module 01-Lesson 05_Data Quality/04. Sources of Dirty Data-h12MQ3d1Z1Y.ar.vtt
2.5 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.ja.vtt
2.5 kB
Part 11-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data-x2dmBUEKQIA.pt-BR.vtt
2.5 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/06. Choosing Metrics-mOH45PzylKk.pt-BR.vtt
2.5 kB
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-7CVlKQ3UjUI.zh-CN.vtt
2.5 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/15. Nest Function-rwDTbptCnM4.pt-BR.vtt
2.5 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/29. Why D3-2qZ3d2WOvwE.en.vtt
2.5 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/03. Facebook Experiment-VqLX0wnrldc.en.vtt
2.5 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/03. How This Lesson Is Structured-xfRtO4aFpv0.zh-CN.vtt
2.5 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/10. Boolean Comparison and Logical Operators-iNNsUJIDtVU.zh-CN.vtt
2.5 kB
Part 13-Module 01-Lesson 07_Narrative Structures/63. Adding Text to the Legend-VPI9MVqGiSM.zh-CN.vtt
2.5 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/45. Fixing the Buttons-NxM_iu4sDxw.zh-CN.vtt
2.5 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/21. Duration vs. Exposure Example-993P7ivCrnQ.ar.vtt
2.5 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/07. Working In The JavaScript Console-cj4kv_dtqY0.zh-CN.vtt
2.5 kB
Part 13-Module 01-Lesson 07_Narrative Structures/05. The Difficulty of Data Visualization-xzo96P5BwSI.ar.vtt
2.5 kB
Part 13-Module 01-Lesson 07_Narrative Structures/47. Creating Axes-3jEbyeW1Re4.pt-BR.vtt
2.5 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/40. Smoothing the Animation with Transitions-9c8he26k_iY.zh-CN.vtt
2.5 kB
Part 05-Module 01-Lesson 05_Data Quality/05. Measuring Data Quality-dj46LqDBFYM.pt-BR.vtt
2.5 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/21. Working with Outliers-4RnQjtJB8t8.pt-BR.vtt
2.5 kB
Part 12-Module 02-Lesson 05_Trees/18. Self-Balancing Trees-EHI548K3jiw.en-US.vtt
2.5 kB
Part 13-Module 01-Lesson 07_Narrative Structures/42. I Love Data Visualization-j24CoLV675I.en.vtt
2.5 kB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/41. Types of Designs-IcrYt7Tzccg.pt-BR.vtt
2.5 kB
Part 12-Module 02-Lesson 05_Trees/18. Self-Balancing Trees-EHI548K3jiw.en.vtt
2.5 kB
Part 17-Module 01-Lesson 05_Binomial Distribution/16. Binomial Distribution Conclusion-9gjCYs8f_PU.zh-CN.vtt
2.5 kB
Part 13-Module 01-Lesson 07_Narrative Structures/56. Recap and Data Dependency-00Tz_3_91RU.zh-CN.vtt
2.5 kB
Part 05-Module 01-Lesson 05_Data Quality/09. Auditing Validity-B9vjn8IYaSg.pt-BR.vtt
2.5 kB
Part 05-Module 01-Lesson 05_Data Quality/07. A Blueprint for Cleaning-3S73cNbhuAk.zh-CN.vtt
2.5 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/14. Common Types of Hypothesis Tests-8hv8KnvQ6JY.pt-BR.vtt
2.5 kB
Part 05-Module 01-Lesson 05_Data Quality/16. Auditing Consistency-bCAkWxApvQM.ar.vtt
2.5 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/03. Setting Up Hypotheses - Part I-NpZxJg4S6X4.en.vtt
2.5 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/04. Why MongoDB-jjMw4Ju-1CM.zh-CN.vtt
2.5 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.pt-BR.vtt
2.5 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-93y6ms_fuQQ.ar.vtt
2.5 kB
Part 11-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data-x2dmBUEKQIA.zh-CN.vtt
2.5 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-nsG26Dz9z44.ar.vtt
2.5 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/10. NumPy Index Arrays-93y6ms_fuQQ.ar.vtt
2.5 kB
Part 13-Module 01-Lesson 05_Dimple.js/06. Dimple Bar Chart Code Overview-vuxN6EC_gso.ar.vtt
2.5 kB
Part 21-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.pt-BR.vtt
2.5 kB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Aggregates in Window Functions-Dxew5w3VF7k.pt-BR.vtt
2.5 kB
Part 11-Module 01-Lesson 07_Regressions/30. R Squared Metric for Regression-yDJEP-XSWdU.ar.vtt
2.5 kB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/09. Notation Continued-ZeGnkrKZWBQ.zh-CN.vtt
2.5 kB
Part 13-Module 01-Lesson 04_Design Principles/31. Red Green Color Blindness-iqbqj9kbapM.pt-BR.vtt
2.5 kB
Part 09-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.en.vtt
2.5 kB
Part 21-Module 01-Lesson 01_Why Python Programming/04. L1 02 Course Overview V4-vFxXSIV5cHM.en.vtt
2.5 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/24. Adjusting the Map Aesthetics-tc1Aai8e-w0.ar.vtt
2.5 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-_Z4d6-d-glM.ar.vtt
2.5 kB
Part 08-Module 01-Lesson 01_Conduct a Job Search/02. Job Search Mindset-cBk7bno3KS0.es-MX.vtt
2.5 kB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.pt-BR.vtt
2.5 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction to Data Wrangling-4cFsT9KBRs8.ar.vtt
2.5 kB
Part 19-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings-98aog0eVcC4.pt-BR.vtt
2.5 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-_Z4d6-d-glM.ar.vtt
2.5 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/26. Klout-3q0oPuWxFpA.zh-CN.vtt
2.5 kB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/23. Pooled Variance Sum of Squares-H-1atcURVzk.pt-BR.vtt
2.5 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/11. Introducing the Working Example-ax7aaLNZkPA.pt-BR.vtt
2.5 kB
Part 08-Module 01-Lesson 01_Conduct a Job Search/02. Job Search Mindset-cBk7bno3KS0.en.vtt
2.5 kB
Part 13-Module 01-Lesson 07_Narrative Structures/42. I Love Data Visualization-j24CoLV675I.pt-BR.vtt
2.5 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-WnQoZzxas-g.en.vtt
2.5 kB
Part 16-Module 03-Lesson 01_Basic SQL/40. NOT Operator-dSQF87oW8a0.pt-BR.vtt
2.5 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-AqlvTMZg6HY.zh-CN.vtt
2.5 kB
Part 11-Module 01-Lesson 04_Decision Trees/34. DT Strengths and Weaknesses-KGnhg76iRfI.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/26. Where are we-d3jQdOuOy8k.en.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/09. Questions and Consent-ZmXg42IoG_Q.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots-GmR3uEM189M.ja.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/55. Attendance at Every World Cup Game-LuCV0YuhoZE.en.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/01. Introduction to JOINs-YvZ010GU-Ck.ar.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/06. Interpreting Multiplie Linear Regression Coefficients-qRD3OVX8UMM.zh-CN.vtt
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Part 11-Module 01-Lesson 16_Tying It All Together/04. Outro-VCNcNnZ6V_s.en.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.pt-BR.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. Assess Intro -vj3CYBlWj3k.en.vtt
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Part 12-Module 01-Lesson 02_Practice Behavioral Questions/08. Time When You Dealt With Failure-Qb4o_4hCuyg.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-80aFO4KmcPM.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/15. Nest Function-rwDTbptCnM4.en.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/17. Collecting Stadium Locations-CqE3Zqv21Wo.en.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-KhGfaSWoEn0.ar.vtt
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Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Using With-OQ-Y0mMjm00.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.ja.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-OzPNbN4L_L0.pt-BR.vtt
2.5 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/43. Table Calculations-VJfCNO0J9jY.en.vtt
2.5 kB
Part 03-Module 01-Lesson 11_L4 Variability/16. Measure Variability-g_V6OCICUUc.pt-BR.vtt
2.5 kB
Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.zh-CN.vtt
2.5 kB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/16. Mean Number of Shoes-j3RQ-8l2nos.pt-BR.vtt
2.5 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/36. Circles with Bound __data__-JeJ_glcExUs.zh-CN.vtt
2.5 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/06. Connecting To Data-WmsAtqbwRI0.zh-CN.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/05. Assignment Operators-p_qfzL-x3Cs.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/40. Creating Time and Attendance Scales-PgAp8ob4hIM.ar.vtt
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Part 09-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.ar.vtt
2.5 kB
Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-X_AS8NBngsk.ar.vtt
2.5 kB
Part 13-Module 01-Lesson 05_Dimple.js/05. A Simple HTTP Server-h8Fa24E_I5s.ar.vtt
2.5 kB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/15. Potential Problems-lGwB6YRThbI.pt-BR.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/02. Hypothesis Testing-9GbHHpiK6wk.pt-BR.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example-Ae_UOATWmDM.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.zh-CN.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/14. Programatic Assessment -Bk_Ve3-4eps.zh-CN.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.en.vtt
2.5 kB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20-YaznAtppruA.pt-BR.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-_Lp_3KUltFk.ar.vtt
2.5 kB
Part 11-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.ja.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces--VxKwVvrNY0.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/22. Encoding Nothing-6bpET1lWVtA.zh-CN.vtt
2.5 kB
Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces--VxKwVvrNY0.pt-BR.vtt
2.5 kB
Part 16-Module 03-Lesson 01_Basic SQL/34. LIKE Operator-O5z6eWkNip4.pt-BR.vtt
2.5 kB
Part 21-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.zh-CN.vtt
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Part 12-Module 01-Lesson 02_Practice Behavioral Questions/07. What Do You Know About the Company-CcTfHemUvbM.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.ja.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/09. Gather Open Jupyter Notebook-IaExjsrVMgQ.en.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/13. Multiple Metrics Example-0eCWo0h5DpM.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.en-US.vtt
2.5 kB
Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.en.vtt
2.5 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/13. Thematic Maps-Jw2q-B2kM9k.en.vtt
2.5 kB
Part 14-Module 01-Lesson 05_Analyzing Results/19. Lessons Learned-5JjCVTc0FGk.zh-CN.vtt
2.5 kB
Part 16-Module 03-Lesson 02_SQL Joins/14. JOINs-CxuHtd1Daqk.pt-BR.vtt
2.5 kB
Part 16-Module 03-Lesson 03_SQL Aggregations/22. Having-D4gmN0vnk58.ar.vtt
2.5 kB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Aggregates in Window Functions-Dxew5w3VF7k.zh-CN.vtt
2.5 kB
Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-OB7iJnEY0Tg.pt-BR.vtt
2.5 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather CSV Files-FpWi4tExVwg.en.vtt
2.5 kB
Part 04-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.pt-BR.vtt
2.5 kB
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.pt-BR.vtt
2.5 kB
Part 16-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.pt-BR.vtt
2.5 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/31. What Do You Get with a Good Klout Score-7N7MBPJKCfw.pt-BR.vtt
2.5 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.pt-BR.vtt
2.5 kB
Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-qHk-FRWnYAo.ar.vtt
2.5 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-KuihzV_LLAE.ar.vtt
2.5 kB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/02. Data Overview-u_qB4w4kL1o.ar.vtt
2.5 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/27. Empirical Variability Bootstrapping-FvtAeWdzy4k.ar.vtt
2.5 kB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Operator-3vLGEuXAAvA.pt-BR.vtt
2.5 kB
Part 17-Module 01-Lesson 11_Confidence Intervals/02. Sampling To Distributions To Confidence Intervals-QYMLkDToigc.pt-BR.vtt
2.5 kB
Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-VkQwfVQ00EQ.ar.vtt
2.5 kB
Part 03-Module 01-Lesson 20_L8 Estimation/19. Engagement Ratio-EdIcXVIYX88.pt-BR.vtt
2.5 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/12. Projection Queries-dFGlIC9nI1Q.pt-BR.vtt
2.5 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.pt-BR.vtt
2.5 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/23. MMs-nCwZE4n4FAs.pt-BR.vtt
2.5 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions-EvhIgrXtOao.ar.vtt
2.5 kB
Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment -YrX-oiFilyA.ar.vtt
2.5 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/12. Iterating on Visualizations-muh0thR2DKo.pt-BR.vtt
2.5 kB
Part 21-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.pt-BR.vtt
2.5 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/23. MMs-nCwZE4n4FAs.zh-Hans.vtt
2.5 kB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Running Totals And Count-rNJwmnzUTxg.zh-CN.vtt
2.5 kB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/06. Resume Review-L3F2BFGYMtI.zh-CN.vtt
2.5 kB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/06. Resume Review-L3F2BFGYMtI.zh-CN.vtt
2.5 kB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/06. Resume Review-L3F2BFGYMtI.zh-CN.vtt
2.5 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.ja.vtt
2.5 kB
Part 13-Module 01-Lesson 07_Narrative Structures/27. Defining a Join-Xo-OJXzS0tQ.zh-CN.vtt
2.5 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/06. Choosing Metrics-mOH45PzylKk.en.vtt
2.5 kB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.pt-BR.vtt
2.5 kB
Part 07-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2-Vvzl2J5K7-Y.pt-BR.vtt
2.5 kB
Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-eAKVYAR_VlY.en.vtt
2.5 kB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/07. Univariate Plots-kgmYLreYB0A.en.vtt
2.5 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.zh-CN.vtt
2.5 kB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.zh-CN.vtt
2.5 kB
Part 11-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.ja.vtt
2.5 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/01. What is Data Visualization-mfLklbVU7r0.en-US.vtt
2.5 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-KYa8_fuZ30w.pt-BR.vtt
2.5 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/06. CSVs in Python-YIDH9HBY3Qk.zh-CN.vtt
2.5 kB
Part 12-Module 02-Lesson 05_Trees/03. Tree Terminology-mPUsDUR_sj8.pt-BR.vtt
2.5 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.en.vtt
2.5 kB
Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-_bnZEnWWqXQ.ar.vtt
2.5 kB
Part 11-Module 01-Lesson 03_SVM/10. SVM in SKlearn-R7xQtQzkvTk.zh-CN.vtt
2.5 kB
Part 11-Module 01-Lesson 16_Tying It All Together/04. Outro-VCNcNnZ6V_s.pt-BR.vtt
2.5 kB
Part 09-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.ja.vtt
2.5 kB
Part 17-Module 01-Lesson 14_Regression/06. Scatter Plots -DvlxZ37O4i8.en.vtt
2.5 kB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/09. Scatter Plots -DvlxZ37O4i8.en.vtt
2.5 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/02. Lesson Overview-1EzlGH4Biu0.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/28. Improving Plots and Sharing Findings-anglRHbmsfw.en.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/11. Introducing the Working Example-ax7aaLNZkPA.en.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/12. Target Population Example-kEFp6xIb8cs.zh-CN.vtt
2.4 kB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/03. 01 Connecting To Data-zuJPPSlbW2c.zh-CN.vtt
2.4 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather Intro-K5ITQn1L1R0.pt-BR.vtt
2.4 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ivBGyL3SzO0.en.vtt
2.4 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/29. Formula for Location of Median-h3zyZHNyreM.pt-BR.vtt
2.4 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/21. Sampling Observations-PsRMReOqccg.ar.vtt
2.4 kB
Part 13-Module 01-Lesson 04_Design Principles/31. Red Green Color Blindness-iqbqj9kbapM.en.vtt
2.4 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.en.vtt
2.4 kB
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8xFV-I4VqZ0.ar.vtt
2.4 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/01. What is Data Visualization-mfLklbVU7r0.en.vtt
2.4 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/27. Communication-P36LwI-R2Vw.ar.vtt
2.4 kB
Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-CvB2qkSk1Zc.ar.vtt
2.4 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.ja.vtt
2.4 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ivBGyL3SzO0.pt-BR.vtt
2.4 kB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/16. Comparing Row to Previous Row-Z_x5ZJyDZog.ar.vtt
2.4 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-5GYA5j1fqBU.zh-CN.vtt
2.4 kB
Part 19-Module 01-Lesson 02_Design/16. General Design Tips-Zq-wMwOfQqY.en.vtt
2.4 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure-CfDLpojt4AY.en.vtt
2.4 kB
Part 03-Module 01-Lesson 20_L8 Estimation/10. 95 CI with Exact Z-Scores-apqUAtnsLZE.en.vtt
2.4 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data-zQj_waidR5w.zh-CN.vtt
2.4 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/06. Other Techniques-KsiyW6bPux8.zh-CN.vtt
2.4 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure-CfDLpojt4AY.pt-BR.vtt
2.4 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/40. Calculated Fields-tR-K9Mvd4B0.zh-CN.vtt
2.4 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/02. Tuskegee and Milgram Experiments-mxNp8_3syVk.pt-BR.vtt
2.4 kB
Part 13-Module 01-Lesson 07_Narrative Structures/50. The Anonymous Accessor Function-I4niz8YMMUM.en.vtt
2.4 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/22. Random Observed Values-KFIt2OC3wCI.zh-CN.vtt
2.4 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.ja.vtt
2.4 kB
Part 12-Module 02-Lesson 05_Trees/20. Tree Rotations-O5Yl-m0YbVA.en-US.vtt
2.4 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Solution --faitcQ7SKs.pt-BR.vtt
2.4 kB
Part 12-Module 02-Lesson 06_Graphs/07. Adjacency Matrices-FsFhoTALA1c.pt-BR.vtt
2.4 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1 Solution -I1enB5CA85Q.zh-CN.vtt
2.4 kB
Part 12-Module 02-Lesson 05_Trees/20. Tree Rotations-O5Yl-m0YbVA.en.vtt
2.4 kB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Window Functions-gp0RPgkDHsQ.zh-CN.vtt
2.4 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge-DMhldSg2_vs.zh-CN.vtt
2.4 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/34. From Source Code to Graphic-PIqgFTee-lk.en.vtt
2.4 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-wqvEtUA0n-s.ar.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Solution -lJEMTES2Ar8.en.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/10. Why Do It in the Database-6vfZYhhmuLU.en.vtt
2.4 kB
Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-hfmvk8DzTGA.zh-CN.vtt
2.4 kB
Part 21-Module 01-Lesson 04_Functions/08. Documentation-_Vl9NJkA6JQ.zh-CN.vtt
2.4 kB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.en-US.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-KYAUEz-50-Q.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-KYAUEz-50-Q.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.ja.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-eeV5K5HKVx4.ar.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.en.vtt
2.4 kB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.en.vtt
2.4 kB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.en.vtt
2.4 kB
Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-GtR3dw2eq2w.pt-BR.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Calculating the Mean-1nzZxmJ8xvU.en.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/04. Algorithm Options-S-cGZ-FEdjQ.zh-CN.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-YZb-Uam-Ics.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/36. Less is More-urgyRvfWPtU.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/34. Comparing Classification and Regression-G_0W912qmGc.zh-CN.vtt
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Part 12-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-R9AtVBq2Z5E.pt-BR.vtt
2.4 kB
Part 17-Module 01-Lesson 11_Confidence Intervals/03. Sampling Distributions Confidence Intervals-gICzUhMVymo.zh-CN.vtt
2.4 kB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-IwcoGtFuYSo.en.vtt
2.4 kB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/08. Time When You Dealt With Failure-Qb4o_4hCuyg.zh-CN.vtt
2.4 kB
Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-YPPQy_eB2mU.pt-BR.vtt
2.4 kB
Part 12-Module 02-Lesson 03_Searching and Sorting/01. Binary Search-0VN5iwEyq4c.en-US.vtt
2.4 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/15. Using mongoimport-JVYH9B6Obpg.zh-CN.vtt
2.4 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-MV_e0z9kFjM.ar.vtt
2.4 kB
Part 21-Module 01-Lesson 03_Control Flow/28. Zip and Enumerate-bSJPzVArE7M.zh-CN.vtt
2.4 kB
Part 12-Module 02-Lesson 03_Searching and Sorting/01. Binary Search-0VN5iwEyq4c.en.vtt
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Part 21-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.en.vtt
2.4 kB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/15. Potential Problems-lGwB6YRThbI.en.vtt
2.4 kB
Part 19-Module 01-Lesson 02_Design/18. Tell A Story-_IdOUEhjVGI.ar.vtt
2.4 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/31. Small Multiples And Dual Axis-bx6MxsoDqsI.pt-BR.vtt
2.4 kB
Part 13-Module 01-Lesson 05_Dimple.js/23. Changing the Date Format-_jOLSNoKxhQ.pt-BR.vtt
2.4 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather CSV Files-FpWi4tExVwg.pt-BR.vtt
2.4 kB
Part 11-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.ja.vtt
2.4 kB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/04. Knapsack Problem--xRKazHGtjU.zh-CN.vtt
2.4 kB
Part 14-Module 01-Lesson 05_Analyzing Results/13. Multiple Metrics Example-0eCWo0h5DpM.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.pt-BR.vtt
2.4 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/12. Iterating on Visualizations-muh0thR2DKo.en.vtt
2.4 kB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML and Trees-766JMEtZCPE.zh-CN.vtt
2.4 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.en.vtt
2.4 kB
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.zh-CN.vtt
2.4 kB
Part 13-Module 01-Lesson 07_Narrative Structures/55. Attendance at Every World Cup Game-LuCV0YuhoZE.pt-BR.vtt
2.4 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/26. Use Measures of Center to Compare-KFK1L4hUW80.ar.vtt
2.4 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps-zSSNWZuVG8Y.zh-CN.vtt
2.4 kB
Part 11-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video-sJzKx_FiMXA.ar.vtt
2.4 kB
Part 13-Module 01-Lesson 07_Narrative Structures/50. The Anonymous Accessor Function-I4niz8YMMUM.pt-BR.vtt
2.4 kB
Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.en.vtt
2.4 kB
Part 13-Module 01-Lesson 04_Design Principles/45. The Grammar of Graphics-AdRbdZhLn04.ar.vtt
2.4 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Introduction to Summary Statistics-PCZmHCrcMcw.en.vtt
2.4 kB
Part 05-Module 01-Lesson 05_Data Quality/09. Auditing Validity-B9vjn8IYaSg.en.vtt
2.4 kB
Part 05-Module 02-Lesson 03_Elements of SQL/03. Types in the SQL World-8swA-PqlEP0.pt-BR.vtt
2.4 kB
Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-OB7iJnEY0Tg.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.pt-BR.vtt
2.4 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/27. L2 04 Tuples V3-33xN-AbTMoc.en.vtt
2.4 kB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.en.vtt
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Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-XDvus8zHJbA.en.vtt
2.4 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-f7vNKm0Zci0.pt-BR.vtt
2.4 kB
Part 18-Module 02-Lesson 01_Gathering Data/05. Source Files On Hand-PjP-EaeXTiY.ar.vtt
2.4 kB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components-AiFcaHRGdEA.zh-CN.vtt
2.4 kB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components-AiFcaHRGdEA.zh-CN.vtt
2.4 kB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components-AiFcaHRGdEA.zh-CN.vtt
2.4 kB
Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-jKZAcZw9xLA.pt-BR.vtt
2.4 kB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites-0ANDJ8i_deE.ar.vtt
2.4 kB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-XDvus8zHJbA.pt-BR.vtt
2.4 kB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-cgWAzXtglF0.es.vtt
2.4 kB
Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results-ZFn9xVQ0hD4.zh-CN.vtt
2.4 kB
Part 13-Module 01-Lesson 05_Dimple.js/12. Creating and Drawing the Chart-ZyhYNaRqqL0.zh-CN.vtt
2.4 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/26. Where are we-d3jQdOuOy8k.pt-BR.vtt
2.4 kB
Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.pt-BR.vtt
2.4 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/01. Introduction-aAmMK8tGEYc.ar.vtt
2.4 kB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/17. Type And Quality Plot - Part 2-Ui1rF6McOBA.pt-BR.vtt
2.4 kB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/41. Types of Designs-IcrYt7Tzccg.en.vtt
2.4 kB
Part 12-Module 02-Lesson 05_Trees/20. Tree Rotations-O5Yl-m0YbVA.pt-BR.vtt
2.4 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/22. L2 07 Lists And Membership Operators II V3-3Nj-b-ZzqH8.pt-BR.vtt
2.4 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/12. Projection Queries-dFGlIC9nI1Q.en.vtt
2.4 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/23. MMs-nCwZE4n4FAs.zh-CN.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/17. -zDs_pN7G-wQ.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/64. All World Cup Games Recap-tVtEEL5i_BE.pt-BR.vtt
2.4 kB
Part 11-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.pt-BR.vtt
2.4 kB
Part 11-Module 01-Lesson 11_Text Learning/14. Why Upweight Rare Words-xYQb6f1SIEk.en.vtt
2.4 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.pt-BR.vtt
2.4 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.en.vtt
2.4 kB
Part 21-Module 01-Lesson 03_Control Flow/02. If Statements-jWiIUMrwPqA.zh-CN.vtt
2.4 kB
Part 05-Module 01-Lesson 05_Data Quality/13. Auditing Accuracy-mADDYP7ldl4.ar.vtt
2.4 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/09. Gather Open Jupyter Notebook-IaExjsrVMgQ.pt-BR.vtt
2.4 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.es.vtt
2.4 kB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.es.vtt
2.4 kB
Part 08-Module 01-Lesson 01_Conduct a Job Search/01. Introduction-axcFtHK6If4.en.vtt
2.4 kB
Part 16-Module 03-Lesson 02_SQL Joins/14. JOINs-CxuHtd1Daqk.en.vtt
2.4 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-vuu3BY7X9ps.pt-BR.vtt
2.4 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.pt-BR.vtt
2.4 kB
Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-OzPNbN4L_L0.en.vtt
2.4 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-WkInrWZwbNA.pt-BR.vtt
2.4 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -oWu4UDkPmj8.en.vtt
2.4 kB
Part 09-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.en.vtt
2.4 kB
Part 14-Module 01-Lesson 05_Analyzing Results/12. Multiple Metrics Introduction-dw0UylGwPe8.pt-BR.vtt
2.4 kB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/05. Resume Reflection-8Cj_tCp8mls.en.vtt
2.4 kB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection-8Cj_tCp8mls.en.vtt
2.4 kB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection-8Cj_tCp8mls.en.vtt
2.4 kB
Part 13-Module 01-Lesson 07_Narrative Structures/64. All World Cup Games Recap-tVtEEL5i_BE.en.vtt
2.4 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-vsLtePFaOFY.zh-CN.vtt
2.4 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.ja.vtt
2.4 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-vsLtePFaOFY.zh-CN.vtt
2.4 kB
Part 11-Module 01-Lesson 12_Feature Selection/16. Lasso Regression-qU1_cj4LfLY.zh-CN.vtt
2.4 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/02. Tuskegee and Milgram Experiments-mxNp8_3syVk.en.vtt
2.4 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1-J4X9r0EGH3k.zh-CN.vtt
2.4 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.pt-BR.vtt
2.4 kB
Part 13-Module 01-Lesson 07_Narrative Structures/32. From Dimple to D3-0yJzBWRQi5U.ar.vtt
2.4 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-3pT4mwTqxoA.ar.vtt
2.4 kB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/14. What is plot.ly-ZRiAWz-sVlM.zh-CN.vtt
2.4 kB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/18. 39. SAD-tya_avP-hKc.en.vtt
2.4 kB
Part 05-Module 02-Lesson 03_Elements of SQL/10. Why Do It in the Database-6vfZYhhmuLU.zh-CN.vtt
2.4 kB
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.ar.vtt
2.4 kB
Part 21-Module 01-Lesson 05_Scripting/13. Handling Error Specifying Exceptions-EHW5I7shdJg.pt-BR.vtt
2.4 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/18. Combining Pandas DataFrames-vB_Et1hz_2M.en.vtt
2.4 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/18. Combining Pandas DataFrames-vB_Et1hz_2M.en.vtt
2.4 kB
Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.ar.vtt
2.4 kB
Part 13-Module 01-Lesson 07_Narrative Structures/47. Creating Axes-3jEbyeW1Re4.en.vtt
2.4 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.en.vtt
2.4 kB
Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-MEtIAGKweXU.ar.vtt
2.4 kB
Part 12-Module 02-Lesson 06_Graphs/07. Adjacency Matrices-FsFhoTALA1c.en-US.vtt
2.4 kB
Part 13-Module 01-Lesson 04_Design Principles/14. Common and Less Common Charts on plot.ly-V9xxdiwJtWk.pt-BR.vtt
2.4 kB
Part 15-Module 01-Lesson 02_Design Principles/06. Gráficos Comuns e Menos Comuns no plot.ly-V9xxdiwJtWk.pt-BR.vtt
2.4 kB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.en.vtt
2.4 kB
Part 19-Module 01-Lesson 02_Design/14. Designing for Color Blindness-k4iTzS7t2U4.ar.vtt
2.4 kB
Part 17-Module 01-Lesson 06_Conditional Probability/01. Introduction to Conditional Probability-Ok8948Wcbmo.ar.vtt
2.4 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-R5EsIDJ0apw.pt-BR.vtt
2.4 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/17. Shape of Distributions-UnN99AAYf8k.zh-CN.vtt
2.4 kB
Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files from the Internet-UceKUJ07Bn8.ar.vtt
2.4 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.pt-BR.vtt
2.4 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.ar.vtt
2.4 kB
Part 12-Module 02-Lesson 05_Trees/12. BSTs-abRNGLhGUmE.zh-CN.vtt
2.4 kB
Part 12-Module 02-Lesson 06_Graphs/07. Adjacency Matrices-FsFhoTALA1c.en.vtt
2.4 kB
Part 13-Module 01-Lesson 07_Narrative Structures/48. Adding the Axes to the Page-B3qrRUamyUs.en.vtt
2.4 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-tfhsgVCX2Ao.pt-BR.vtt
2.4 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.pt-BR.vtt
2.4 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.ar.vtt
2.4 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/16. Using A Confidence Interval to Make A Decision-MghT95b6LbQ.zh-CN.vtt
2.4 kB
Part 12-Module 02-Lesson 02_List-Based Collections/09. Stacks Details-HpaVHzDeZC4.en-US.vtt
2.4 kB
Part 14-Module 01-Lesson 05_Analyzing Results/12. Multiple Metrics Introduction-dw0UylGwPe8.en.vtt
2.4 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/01. Introduction-QXxtu_gdWQs.ar.vtt
2.4 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/05. Tabular Formats-5Vq530Lijb0.pt-BR.vtt
2.4 kB
Part 09-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.ja.vtt
2.4 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/02. Introduction-QXxtu_gdWQs.ar.vtt
2.4 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.ja.vtt
2.3 kB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/07. What Do You Know About the Company-CcTfHemUvbM.en.vtt
2.3 kB
Part 12-Module 02-Lesson 02_List-Based Collections/09. Stacks Details-HpaVHzDeZC4.en.vtt
2.3 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-Z4n3jR-FZP8.zh-CN.vtt
2.3 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.ja.vtt
2.3 kB
Part 11-Module 01-Lesson 16_Tying It All Together/02. Summary-avqZaTECZTQ.zh-CN.vtt
2.3 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/20. Outliers-HKIsvkZUZfo.zh-CN.vtt
2.3 kB
Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-FT0dM2um34E.pt-BR.vtt
2.3 kB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/05. Cleaning With More Advanced String Functions-E6cK8RbYGEc.en.vtt
2.3 kB
Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-FT0dM2um34E.en.vtt
2.3 kB
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-_7Vqou7k7fI.pt-BR.vtt
2.3 kB
Part 16-Module 03-Lesson 01_Basic SQL/43. AND BETWEEN Operators-nBuDPneWcKY.en.vtt
2.3 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.pt-BR.vtt
2.3 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather Intro-K5ITQn1L1R0.en.vtt
2.3 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-O0zo3-NtBSI.es.vtt
2.3 kB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-O0zo3-NtBSI.es.vtt
2.3 kB
Part 12-Module 02-Lesson 05_Trees/18. Self-Balancing Trees-EHI548K3jiw.pt-BR.vtt
2.3 kB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/19. Between 10 and 16-4QIEdzv6g6w.en.vtt
2.3 kB
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.en.vtt
2.3 kB
Part 13-Module 01-Lesson 05_Dimple.js/13. Adding an Axis with Dimple-7okDT6V9Mmk.ar.vtt
2.3 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/18. Averaging Locations-GLQJukg-0fQ.ar.vtt
2.3 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/05. Setting Up Hypotheses - Part II-nByvHz77GiA.zh-CN.vtt
2.3 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/29. Data Analysis and Related Terms-9g9_tlhbNSw.zh-CN.vtt
2.3 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-LlPsmQx5y50.pt-BR.vtt
2.3 kB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/07. DF - Sample SD-Jfk3egev9UM.zh-CN.vtt
2.3 kB
Part 08-Module 01-Lesson 01_Conduct a Job Search/02. Job Search Mindset-cBk7bno3KS0.zh-CN.vtt
2.3 kB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.ar.vtt
2.3 kB
Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-XZNKM3xMZNY.pt-BR.vtt
2.3 kB
Part 11-Module 01-Lesson 14_Validation/15. Validation Mini-Project Video-dlbeMlRoFd4.ar.vtt
2.3 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/25. L2 05 Lists Methods V1-WXkPm4rv6ng.pt-BR.vtt
2.3 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/14. The Central Limit Theorem-ag3TB5UGu_g.pt-BR.vtt
2.3 kB
Part 07-Module 01-Lesson 01_GitHub Review/01. Introduction-Vnj2VNQROtI.ar.vtt
2.3 kB
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-NXbR9GQbtnk.ar.vtt
2.3 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-UkGwgerJU44.zh-CN.vtt
2.3 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-KYa8_fuZ30w.en.vtt
2.3 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-k8Ru6RQJbd4.ar.vtt
2.3 kB
Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-B_fHrMIzIgE.pt-BR.vtt
2.3 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/30. Filtering-vXGDYzAo22Y.ar.vtt
2.3 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-k8Ru6RQJbd4.ar.vtt
2.3 kB
Part 12-Module 02-Lesson 05_Trees/08. Search and Delete-KbL-HK3ztX8.en-US.vtt
2.3 kB
Part 11-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.en.vtt
2.3 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-WGD8AWQg9dE.pt-BR.vtt
2.3 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.pt-BR.vtt
2.3 kB
Part 11-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.pt-BR.vtt
2.3 kB
Part 12-Module 02-Lesson 05_Trees/08. Search and Delete-KbL-HK3ztX8.en.vtt
2.3 kB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/17. Type And Quality Plot - Part 2-Ui1rF6McOBA.en.vtt
2.3 kB
Part 11-Module 01-Lesson 09_Clustering/11. K-Means Clustering Visualization 3-WfwX3B4d8_I.zh-CN.vtt
2.3 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-Hs3__UsSyL8.zh-CN.vtt
2.3 kB
Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-GtR3dw2eq2w.en.vtt
2.3 kB
Part 09-Module 01-Lesson 02_R Basics/15. Data Munging-q_Ghc6VsDo0.ar.vtt
2.3 kB
Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.en.vtt
2.3 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/08. Self JOINs-tw_VzEGBOvI.en.vtt
2.3 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/18. Combining Pandas DataFrames-vB_Et1hz_2M.pt-BR.vtt
2.3 kB
Part 08-Module 01-Lesson 01_Conduct a Job Search/01. Introduction-axcFtHK6If4.pt-BR.vtt
2.3 kB
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-GuBics_6HOk.zh-CN.vtt
2.3 kB
Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-YPPQy_eB2mU.en.vtt
2.3 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/09. -zWNcZ-7k7Tw.en-US.vtt
2.3 kB
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.ar.vtt
2.3 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/18. Combining Pandas DataFrames-vB_Et1hz_2M.pt-BR.vtt
2.3 kB
Part 11-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.ja.vtt
2.3 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/02. Histograms-4t10RgUv2Fc.ar.vtt
2.3 kB
Part 17-Module 01-Lesson 16_Logistic Regression/06. Interpreting Results-UPOxxbKu6CQ.pt-BR.vtt
2.3 kB
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-t0iflCpBUDA.ar.vtt
2.3 kB
Part 13-Module 01-Lesson 04_Design Principles/40. Lie Factor-jkR2kIJrvBM.pt-BR.vtt
2.3 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-XUZIGbX3JIg.ar.vtt
2.3 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/09. -zWNcZ-7k7Tw.en.vtt
2.3 kB
Part 05-Module 02-Lesson 03_Elements of SQL/03. Types in the SQL World-8swA-PqlEP0.en.vtt
2.3 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/22. in Operator-8iX-7hwKX1Q.ar.vtt
2.3 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.pt-BR.vtt
2.3 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/04. Iterative Process-m2qDeWrGIDI.ar.vtt
2.3 kB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/01. Intro-vek87HVWexE.pt-BR.vtt
2.3 kB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/01. Intro-vek87HVWexE.pt-BR.vtt
2.3 kB
Part 13-Module 01-Lesson 04_Design Principles/40. Lie Factor-jkR2kIJrvBM.en-US.vtt
2.3 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Notation for the Mean-3EF15AoRxyM.pt-BR.vtt
2.3 kB
Part 03-Module 01-Lesson 13_L5 Standardizing/17. Z-Score-pftNHu4uevA.en.vtt
2.3 kB
Part 13-Module 01-Lesson 07_Narrative Structures/11. Personal Data Visualization-NtFICAw7tW4.zh-CN.vtt
2.3 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-WkInrWZwbNA.en.vtt
2.3 kB
Part 17-Module 01-Lesson 11_Confidence Intervals/02. Sampling To Distributions To Confidence Intervals-QYMLkDToigc.en.vtt
2.3 kB
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-_7Vqou7k7fI.en.vtt
2.3 kB
Part 09-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.pt-BR.vtt
2.3 kB
Part 11-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.ar.vtt
2.3 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/02. Hypothesis Testing-9GbHHpiK6wk.zh-CN.vtt
2.3 kB
Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces--VxKwVvrNY0.en.vtt
2.3 kB
Part 12-Module 02-Lesson 05_Trees/03. Tree Terminology-mPUsDUR_sj8.zh-CN.vtt
2.3 kB
Part 13-Module 01-Lesson 04_Design Principles/40. Lie Factor-jkR2kIJrvBM.en.vtt
2.3 kB
Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces--VxKwVvrNY0.en.vtt
2.3 kB
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-UjyPKvNHz4A.ar.vtt
2.3 kB
Part 13-Module 01-Lesson 07_Narrative Structures/48. Adding the Axes to the Page-B3qrRUamyUs.pt-BR.vtt
2.3 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/24. There Must Be A Better Way-oBp8YX2AgJw.ar.vtt
2.3 kB
Part 11-Module 01-Lesson 07_Regressions/20. Extracting Score Data from sklearn-NhD4oUuhvO8.zh-CN.vtt
2.3 kB
Part 13-Module 01-Lesson 04_Design Principles/35. Chartjunk-jm2qOX2Q2HQ.en.vtt
2.3 kB
Part 15-Module 01-Lesson 02_Design Principles/16. Gráfico Lixo-jm2qOX2Q2HQ.en.vtt
2.3 kB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/18. 08 Table Calculations-Vkf3Ft93zMc.pt-BR.vtt
2.3 kB
Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-GTLvqNrAETc.ar.vtt
2.3 kB
Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-gBdKhmtrtG8.ar.vtt
2.3 kB
Part 13-Module 01-Lesson 04_Design Principles/47. Discovery versus Presentation-znQ3iBhhJtA.zh-CN.vtt
2.3 kB
Part 16-Module 03-Lesson 03_SQL Aggregations/03. Data Types and NULLs-RgTcYwKqtYI.en.vtt
2.3 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/29. L2 03 Sets V2-eIHNFgTFfnA.en.vtt
2.3 kB
Part 17-Module 01-Lesson 16_Logistic Regression/07. Interpreting Results in Python-IY88UTiJltQ.zh-CN.vtt
2.3 kB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-EtWewV65zbs.pt-BR.vtt
2.3 kB
Part 16-Module 03-Lesson 01_Basic SQL/24. WHERE Statements -mN0uTnlXaxg.en.vtt
2.3 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure-CfDLpojt4AY.zh-CN.vtt
2.3 kB
Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.zh-CN.vtt
2.3 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/26. Confidence Interval Case Breakdown-gycmvQqw-8s.pt-BR.vtt
2.3 kB
Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI-L_JV4fbRAfA.pt-BR.vtt
2.3 kB
Part 09-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer-SsNYXdi3q-I.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/20. Building the Linear Model-zyIc0sXYk2A.ja.vtt
2.3 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/37. setInterval and clearInterval-r1sgfqg85us.zh-CN.vtt
2.3 kB
Part 11-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.en.vtt
2.3 kB
Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-OGK9SHt8SWg.pt-BR.vtt
2.3 kB
Part 11-Module 01-Lesson 13_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.pt-BR.vtt
2.3 kB
Part 08-Module 01-Lesson 01_Conduct a Job Search/01. Introduction-axcFtHK6If4.es-MX.vtt
2.3 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/08. Self JOINs-tw_VzEGBOvI.pt-BR.vtt
2.3 kB
Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-tfYAGBIR_Ws.zh-CN.vtt
2.3 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/10. Calculate SDs-bjk5m0wrj3w.pt-BR.vtt
2.3 kB
Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-WZRsqdNrC1A.pt-BR.vtt
2.3 kB
Part 12-Module 02-Lesson 05_Trees/17. Heap Implementation-2LAdml6_pDY.pt-BR.vtt
2.3 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/03. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.zh-CN.vtt
2.3 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/04. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.zh-CN.vtt
2.3 kB
Part 12-Module 02-Lesson 06_Graphs/03. Directions and Cycles-lF0vUktQDPo.zh-CN.vtt
2.3 kB
Part 21-Module 01-Lesson 05_Scripting/02. Python Installation-2_P05aYChqQ.ar.vtt
2.3 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -oWu4UDkPmj8.pt-BR.vtt
2.3 kB
Part 18-Module 02-Lesson 01_Gathering Data/17. JSON Files In Python-8JdUknZP59Q.ar.vtt
2.3 kB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-cgWAzXtglF0.en.vtt
2.3 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/28. Probability of Obtaining Mean-ErwocwQVgYE.pt-BR.vtt
2.3 kB
Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-80aFO4KmcPM.en.vtt
2.3 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-P6ZOr7JiMLk.ar.vtt
2.3 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-EwV5Vs2m33w.zh-CN.vtt
2.3 kB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.zh-CN.vtt
2.3 kB
Part 12-Module 02-Lesson 05_Trees/13. BST Complications-pcB0wV7myy4.zh-CN.vtt
2.3 kB
Part 11-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.en.vtt
2.3 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/08. Continuous vs. Discrete Data-BzgZebZD9kk.ar.vtt
2.3 kB
Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-8ZvLpWDITn4.ar.vtt
2.3 kB
Part 12-Module 02-Lesson 06_Graphs/11. BFS-pol4kGNlvJA.en.vtt
2.3 kB
Part 18-Module 02-Lesson 01_Gathering Data/08. Source Scraping Webpages-ZqTad6Usf9g.ar.vtt
2.3 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-O0zo3-NtBSI.pt-BR.vtt
2.3 kB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-O0zo3-NtBSI.pt-BR.vtt
2.3 kB
Part 05-Module 01-Lesson 05_Data Quality/05. Measuring Data Quality-dj46LqDBFYM.zh-CN.vtt
2.3 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.en.vtt
2.3 kB
Part 11-Module 01-Lesson 15_Evaluation Metrics/04. Picking the Most Suitable Metric-GAfPvj2SSiE.ar.vtt
2.3 kB
Part 12-Module 02-Lesson 06_Graphs/11. BFS-pol4kGNlvJA.en-US.vtt
2.3 kB
Part 13-Module 01-Lesson 04_Design Principles/24. Redundant Encodings-RU3rI_pO8Rc.ar.vtt
2.3 kB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.pt-BR.vtt
2.3 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.zh-CN.vtt
2.3 kB
Part 16-Module 03-Lesson 03_SQL Aggregations/03. Data Types and NULLs-RgTcYwKqtYI.pt-BR.vtt
2.3 kB
Part 19-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings-98aog0eVcC4.en.vtt
2.3 kB
Part 11-Module 01-Lesson 16_Tying It All Together/01. Introduction-8tm1144C4T0.pt-BR.vtt
2.3 kB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/02. Multiple Linear Regression-rvYZp99nj6c.zh-CN.vtt
2.3 kB
Part 21-Module 01-Lesson 05_Scripting/05. Running A Python Script-vMKemwCderg.en.vtt
2.3 kB
Part 03-Module 01-Lesson 11_L4 Variability/39. Clarifying Sample SD-iRudjk53deY.es.vtt
2.3 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-0XM5ILuCg1k.en.vtt
2.3 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 1-APRpwqFpGwI.ar.vtt
2.3 kB
Part 03-Module 01-Lesson 11_L4 Variability/39. Clarifying Sample SD-iRudjk53deY.ab.vtt
2.3 kB
Part 12-Module 02-Lesson 06_Graphs/06. Graph Representations-uw9u6dtl0WA.zh-CN.vtt
2.3 kB
Part 16-Module 03-Lesson 01_Basic SQL/40. NOT Operator-dSQF87oW8a0.en.vtt
2.3 kB
Part 16-Module 03-Lesson 03_SQL Aggregations/01. Introduction to Aggregations-5vRf_Ntoxfw.zh-CN.vtt
2.3 kB
Part 17-Module 01-Lesson 11_Confidence Intervals/12. Other Language Associated With Confidence Intervals-9KYVRx7-llg.en.vtt
2.3 kB
Part 17-Module 01-Lesson 14_Regression/10. What Defines A Line-lTqwhsSNP2c.zh-CN.vtt
2.3 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/21. One tailed or two tailed-Cf8PvkUR1NQ.zh-CN.vtt
2.3 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/22. Scraping Solution-J1gn4ZBLkt4.en.vtt
2.3 kB
Part 12-Module 02-Lesson 04_Maps and Hashing/02. Sets and Maps-gmIb-qZhTDQ.en-US.vtt
2.3 kB
Part 13-Module 01-Lesson 07_Narrative Structures/20. The Martini Glass-h8b8SOsSiT4.ar.vtt
2.3 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/01. Intro to MongoDB-GfK7GW3V-W0.pt-BR.vtt
2.3 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/21. Querying Arrays Using Scalars-8uhfnWgiBHM.ar.vtt
2.3 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/03. Developer Tools and Console-C2Ob9vkpQ7g.en-US.vtt
2.3 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/09. Maps in D3-DAfs_MCYP0o.ar.vtt
2.3 kB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/04. Time When You Showed Initiative-29mkriaGT0E.pt-BR.vtt
2.3 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/07. Packages Overview-sCQoQsmI3F0.zh-CN.vtt
2.3 kB
Part 12-Module 02-Lesson 04_Maps and Hashing/02. Sets and Maps-gmIb-qZhTDQ.en.vtt
2.3 kB
Part 03-Module 01-Lesson 11_L4 Variability/24. Formula for Avg. Abs. Dev.-ihC1Pm8E8gU.zh-CN.vtt
2.3 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/03. Developer Tools and Console-C2Ob9vkpQ7g.en.vtt
2.3 kB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-9piyE5in7YE.pt-BR.vtt
2.3 kB
Part 08-Module 01-Lesson 01_Conduct a Job Search/01. Introduction-axcFtHK6If4.zh-CN.vtt
2.3 kB
Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.en.vtt
2.3 kB
Part 18-Module 02-Lesson 01_Gathering Data/08. Scraping Webpages -bAeGbBBAIkE.en.vtt
2.3 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.en.vtt
2.3 kB
Part 17-Module 01-Lesson 13_Case Study AB tests/04. Business Example-Wzz7omSDfEk.pt-BR.vtt
2.3 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/07. What is the Standard Deviation Measuring-IbwUJ3ORZ5s.zh-CN.vtt
2.3 kB
Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.pt-BR.vtt
2.3 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/06. 5 Number Summary to Variance-Ljhau0hrZ1g.ar.vtt
2.3 kB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-EtWewV65zbs.en.vtt
2.3 kB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/11. Z-Table-hSAxcGBxbds.pt-BR.vtt
2.3 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/28. Multiple Testing Corrections-DuMgeHrkIF0.en.vtt
2.3 kB
Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-CvTXyvw7QLc.ja.vtt
2.3 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/28. Multiple Testing Corrections-DuMgeHrkIF0.pt-BR.vtt
2.3 kB
Part 18-Module 04-Lesson 01_Cleaning Data/20. Conclusion -d_nKtLo5WYA.ar.vtt
2.3 kB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.pt-BR.vtt
2.3 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-zovzbp_Rpu4.pt-BR.vtt
2.3 kB
Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files-w-ZG6DMkVi4.zh-CN.vtt
2.3 kB
Part 03-Module 01-Lesson 20_L8 Estimation/19. Engagement Ratio-vpwCy5Gphrw.pt-BR.vtt
2.3 kB
Part 16-Module 03-Lesson 03_SQL Aggregations/30. CASE Statements and Aggregations-asSXB6iD3z4.ar.vtt
2.3 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-R5EsIDJ0apw.en.vtt
2.3 kB
Part 13-Module 01-Lesson 04_Design Principles/03. Parts of Speech Analogy for Data Vis-bO8clma7Mnc.pt-BR.vtt
2.3 kB
Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-UMWsyRYnfPk.ar.vtt
2.3 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/23. The Radius Scale-Rkrj1HjaMQM.ar.vtt
2.3 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-vuu3BY7X9ps.en.vtt
2.3 kB
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.ar.vtt
2.3 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/32. What Happened-NSuT87J4V-g.pt-BR.vtt
2.3 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/11. Data Vis in Data Science-e_-61K3jK1Y.ar.vtt
2.3 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. Assess Intro -vj3CYBlWj3k.zh-CN.vtt
2.3 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Programmatic Data Cleaning Process-9-T1CFuOqdQ.ar.vtt
2.3 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/22. Comparing the Two Student Groups-eM82u21V7AM.en.vtt
2.3 kB
Part 11-Module 01-Lesson 13_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.en.vtt
2.3 kB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/20. When Does the CLT Not Work-uZGTVUEMfrU.ar.vtt
2.3 kB
Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-VYwgHHqaUII.zh-CN.vtt
2.3 kB
Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.zh-CN.vtt
2.3 kB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/16. Mean Number of Shoes-j3RQ-8l2nos.en.vtt
2.3 kB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/23. Pooled Variance Sum of Squares-H-1atcURVzk.en.vtt
2.3 kB
Part 06-Module 01-Lesson 03_Analyzing Data/07. Aggregation Operators 2-UZMklqP5-p4.pt-BR.vtt
2.3 kB
Part 12-Module 02-Lesson 05_Trees/05. Tree Traversal-KZOdmzypynw.zh-CN.vtt
2.3 kB
Part 09-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.zh-CN.vtt
2.3 kB
Part 12-Module 02-Lesson 04_Maps and Hashing/02. Sets and Maps-gmIb-qZhTDQ.pt-BR.vtt
2.3 kB
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.th.vtt
2.3 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/09. Gather Open Jupyter Notebook-IaExjsrVMgQ.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/14. Common and Less Common Charts on plot.ly-V9xxdiwJtWk.en.vtt
2.2 kB
Part 15-Module 01-Lesson 02_Design Principles/06. Gráficos Comuns e Menos Comuns no plot.ly-V9xxdiwJtWk.en.vtt
2.2 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/23. Connecting Errors and P-Values-hFNjd5l9CLs.en.vtt
2.2 kB
Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-jKZAcZw9xLA.en.vtt
2.2 kB
Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6-eqFgLu0eqBE.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.ar.vtt
2.2 kB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/31. Dependent Samples-kcTh3hJ1XCw.pt-BR.vtt
2.2 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.en.vtt
2.2 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.zh-CN.vtt
2.2 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.en.vtt
2.2 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.ja.vtt
2.2 kB
Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.ja.vtt
2.2 kB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/04. Gathering Data-r7BHGq_0P9Q.pt-BR.vtt
2.2 kB
Part 06-Module 01-Lesson 03_Analyzing Data/08. Match Operator-FZ8KVv1VOK4.zh-CN.vtt
2.2 kB
Part 11-Module 01-Lesson 02_Naive Bayes/04. Features and Labels Musical Example-rnv0-lG9yKU.ar.vtt
2.2 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators-48AgxPygRuQ.pt-BR.vtt
2.2 kB
Part 17-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data-vhl-SADfti8.ar.vtt
2.2 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.ar.vtt
2.2 kB
Part 11-Module 01-Lesson 16_Tying It All Together/01. Introduction-8tm1144C4T0.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/49. Orienting and Drawing the Axes-I9-ysMlq-Xc.ar.vtt
2.2 kB
Part 17-Module 01-Lesson 11_Confidence Intervals/05. Confidence Interval for a Difference In Means-8hrWGzjyhck.en.vtt
2.2 kB
Part 19-Module 01-Lesson 02_Design/07. Chart Junk-3BTBEYOG2o8.pt-BR.vtt
2.2 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/22. Comparing the Two Student Groups-eM82u21V7AM.pt-BR.vtt
2.2 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-iu6CxSkq-wg.ar.vtt
2.2 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.ar.vtt
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.pt-BR.vtt
2.2 kB
Part 12-Module 02-Lesson 05_Trees/17. Heap Implementation-2LAdml6_pDY.zh-CN.vtt
2.2 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/43. Table Calculations-VJfCNO0J9jY.zh-CN.vtt
2.2 kB
Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-StmEUgT1XSY.pt-BR.vtt
2.2 kB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.hi.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/07. The One Thing SQL is Terrible At-wrjCB1abNyM.ar.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots-GmR3uEM189M.zh-CN.vtt
2.2 kB
Part 13-Module 01-Lesson 04_Design Principles/35. Chartjunk-jm2qOX2Q2HQ.pt-BR.vtt
2.2 kB
Part 15-Module 01-Lesson 02_Design Principles/16. Gráfico Lixo-jm2qOX2Q2HQ.pt-BR.vtt
2.2 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-O0zo3-NtBSI.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-O0zo3-NtBSI.en.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/14. Common Types of Hypothesis Tests-8hv8KnvQ6JY.zh-CN.vtt
2.2 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/22. Scraping Solution-J1gn4ZBLkt4.pt-BR.vtt
2.2 kB
Part 09-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots-llvIDIu3Sw8.pt-BR.vtt
2.2 kB
Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-XZNKM3xMZNY.en.vtt
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/17. Type And Quality Plot - Part 2-Ui1rF6McOBA.zh-CN.vtt
2.2 kB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/02. What's Ahead-ggbCydfI1JM.pt-BR.vtt
2.2 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-0XM5ILuCg1k.pt-BR.vtt
2.2 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-3kH4ei9l4h8.ar.vtt
2.2 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-j0qfuunqym8.pt-BR.vtt
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Part 21-Module 01-Lesson 04_Functions/11. L4 08 Lambda Expressions V3-wkEmPz1peJM.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer-SsNYXdi3q-I.en.vtt
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Part 21-Module 01-Lesson 01_Why Python Programming/04. L1 02 Course Overview V4-vFxXSIV5cHM.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/35. Point of SD-d-_ZKyocTDw.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.en.vtt
2.2 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/19. Pooled Standard Error-iub8yWiO84I.pt-BR.vtt
2.2 kB
Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-StmEUgT1XSY.en.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/06. Why Businesses Choose Databases-j4ey7--h9r8.en.vtt
2.2 kB
Part 18-Module 02-Lesson 01_Gathering Data/22. Why Businesses Choose Databases-j4ey7--h9r8.en.vtt
2.2 kB
Part 09-Module 01-Lesson 01_What is EDA/09. Course Overview-W8N0aSMPff8.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.en.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators-48AgxPygRuQ.en.vtt
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Part 12-Module 02-Lesson 05_Trees/20. Tree Rotations-O5Yl-m0YbVA.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/18. Author-driven Examples-mr2HGcqk3nU.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/60. Context for the Reader-_GkNEO9qeWI.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-Hb2q-o4ElV4.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/58. Juxtaposition and Comparison-abaD-wvlbkg.ar.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.es-ES.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/26. Confidence Interval Case Breakdown-gycmvQqw-8s.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/17. Inspecting the X-axis-huZPg2gRmLk.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.pt-BR.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/12. Other Language Associated With Confidence Intervals-9KYVRx7-llg.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.en.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/05. Tabular Formats-5Vq530Lijb0.en.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.pt-BR.vtt
2.2 kB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.pt-BR.vtt
2.2 kB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.pt-BR.vtt
2.2 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.zh-CN.vtt
2.2 kB
Part 13-Module 01-Lesson 07_Narrative Structures/42. I Love Data Visualization-j24CoLV675I.zh-CN.vtt
2.2 kB
Part 07-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2-elZCLxVvJrY.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-S1yjJWWza7g.pt-BR.vtt
2.2 kB
Part 13-Module 01-Lesson 04_Design Principles/54. The Spectrum of Tech in Data Vis-4-tLvLvX9U4.zh-CN.vtt
2.2 kB
Part 07-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2-Vvzl2J5K7-Y.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.ar.vtt
2.2 kB
Part 13-Module 01-Lesson 05_Dimple.js/23. Changing the Date Format-_jOLSNoKxhQ.en.vtt
2.2 kB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/15. Finches-ONhDQKYCJlE.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.ja.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/07. Aggregation Operators 2-UZMklqP5-p4.en.vtt
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Part 17-Module 01-Lesson 14_Regression/08. Correlation Coefficients-rL5Bn8Fi-zE.ar.vtt
2.2 kB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/11. Correlation Coefficients-rL5Bn8Fi-zE.ar.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/39. Clarifying Sample SD-iRudjk53deY.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-SwbreslrpqQ.zh-CN.vtt
2.2 kB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/02. Tuskegee and Milgram Experiments-mxNp8_3syVk.zh-CN.vtt
2.2 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/25. L2 05 Lists Methods V1-WXkPm4rv6ng.en.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/09. Handling Attributes-YSEGZMBbxTk.ar.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/35. Point of SD-d-_ZKyocTDw.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/15. Nest Function-rwDTbptCnM4.zh-CN.vtt
2.2 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/17. Performance Tuning 3-hIAE8W6x5O8.ar.vtt
2.2 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-Mta8Hv36k7Q.zh-CN.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/03. Facebook Experiment-VqLX0wnrldc.zh-CN.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-LlPsmQx5y50.en.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-Mta8Hv36k7Q.zh-CN.vtt
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/01. Intro-vek87HVWexE.en.vtt
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/01. Intro-vek87HVWexE.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Intro -FnUrE4dhgh8.ar.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/31. What Do You Get with a Good Klout Score-7N7MBPJKCfw.zh-CN.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/01. Intro to SQL for Data Analysis-CU4igXr9xTw.pt-BR.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-t_ZSrov187k.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/50. Goodbye and Keep Learning-B4EKdtRmv60.ar.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -Vf-EK6vg6Uc.pt-BR.vtt
2.2 kB
Part 11-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.ja.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/29. Why D3-2qZ3d2WOvwE.zh-CN.vtt
2.2 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather CSV Files-FpWi4tExVwg.zh-CN.vtt
2.2 kB
Part 12-Module 02-Lesson 06_Graphs/11. BFS-pol4kGNlvJA.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/08. Map Distortions-xL5xVEuLuNE.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/09. Be Skeptical Outliers and Anomalies-kAisC2wRGBU.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/04. Chart Types-0a5oJR6TwAs.ar.vtt
2.2 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/39. Update the Title-ut83yNUYLmc.en.vtt
2.2 kB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Operator-3vLGEuXAAvA.en.vtt
2.2 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Why the Standard Deviation-XlTBvjQ2t8w.ar.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/29. L2 03 Sets V2-eIHNFgTFfnA.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-EtWewV65zbs.es.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/39. Clarifying Sample SD-iRudjk53deY.en.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/08. Extracting Data-OeiBJ_D-ZsM.ar.vtt
2.2 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/11. Introducing the Working Example-ax7aaLNZkPA.zh-CN.vtt
2.2 kB
Part 13-Module 01-Lesson 07_Narrative Structures/55. Attendance at Every World Cup Game-LuCV0YuhoZE.zh-CN.vtt
2.2 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/21. Working with Outliers-4RnQjtJB8t8.en.vtt
2.2 kB
Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-B_fHrMIzIgE.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/21. Rankings of Visual Encodings-ycsXqX7T80Y.pt-BR.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/08. Rankings of Visual Encodings - Data Visualization and D3.js-ycsXqX7T80Y.pt-BR.vtt
2.2 kB
Part 17-Module 01-Lesson 13_Case Study AB tests/11. Metric - Average Reading Duration-w6Y9ZxHDEbw.zh-CN.vtt
2.2 kB
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8xFV-I4VqZ0.ja.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/02. Lesson Overview-1EzlGH4Biu0.zh-CN.vtt
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Part 17-Module 01-Lesson 14_Regression/16. How Do We Interpret Results-eLk0XGGMaCE.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-WGD8AWQg9dE.en.vtt
2.2 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/12. Variance Standard Deviation Final Points-vXUgp2375j4.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.zh-CN.vtt
2.2 kB
Part 11-Module 01-Lesson 13_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.ar.vtt
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Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules Part II-aASigWQ_XU0.pt-BR.vtt
2.2 kB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/15. Different Bin Sizes-_wOXWBZkL58.en-US.vtt
2.2 kB
Part 11-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.pt-BR.vtt
2.2 kB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/07. Univariate Plots-kgmYLreYB0A.zh-CN.vtt
2.2 kB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/15. Different Bin Sizes-_wOXWBZkL58.en.vtt
2.2 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.ja.vtt
2.2 kB
Part 11-Module 01-Lesson 11_Text Learning/14. Why Upweight Rare Words-xYQb6f1SIEk.pt-BR.vtt
2.2 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Solution -lJEMTES2Ar8.zh-CN.vtt
2.2 kB
Part 21-Module 01-Lesson 05_Scripting/05. Running A Python Script-vMKemwCderg.zh-CN.vtt
2.2 kB
Part 13-Module 01-Lesson 04_Design Principles/31. Red Green Color Blindness-iqbqj9kbapM.zh-CN.vtt
2.2 kB
Part 13-Module 01-Lesson 07_Narrative Structures/50. The Anonymous Accessor Function-I4niz8YMMUM.zh-CN.vtt
2.2 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/29. Formula for Location of Median-h3zyZHNyreM.es.vtt
2.2 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/21. Size vs. Power Trade-Off-bnTIVGBkKhM.ar.vtt
2.2 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/16. Pandas groupby()-w3D0no7E8uw.pt-BR.vtt
2.2 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/24. The Facebook Offering Animation-s7h2tH6z9Rg.ar.vtt
2.2 kB
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-S-pjRUJAGTs.zh-CN.vtt
2.2 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/07. Types Of Errors - Part I-aw6GMxIvENc.en.vtt
2.2 kB
Part 19-Module 01-Lesson 02_Design/07. Chart Junk-3BTBEYOG2o8.en.vtt
2.2 kB
Part 19-Module 01-Lesson 02_Design/16. General Design Tips-Zq-wMwOfQqY.zh-CN.vtt
2.2 kB
Part 21-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.zh-CN.vtt
2.2 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/16. Pandas groupby()-w3D0no7E8uw.pt-BR.vtt
2.2 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.ja.vtt
2.2 kB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20-YaznAtppruA.en.vtt
2.2 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-lVLgiRRhFpQ.pt-BR.vtt
2.2 kB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/18. Multicollinearity VIFs-uiF3UcDWwPI.pt-BR.vtt
2.2 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-lVLgiRRhFpQ.pt-BR.vtt
2.2 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.pt-BR.vtt
2.2 kB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.pt-BR.vtt
2.2 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.ja.vtt
2.2 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.en.vtt
2.2 kB
Part 12-Module 02-Lesson 02_List-Based Collections/05. Linked Lists-zxkpZrozDUk.pt-BR.vtt
2.2 kB
Part 17-Module 01-Lesson 13_Case Study AB tests/05. Experiment I-JLKAdT2JESk.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.es-ES.vtt
2.2 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/08. Map Distortions-xL5xVEuLuNE.pt-BR.vtt
2.2 kB
Part 18-Module 03-Lesson 01_Assessing Data/10. Assessing Vs Exploring V2 -hVFZ6jFKOso.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.zh-CN.vtt
2.2 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Calculating the Mean-1nzZxmJ8xvU.zh-CN.vtt
2.2 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.zh-CN.vtt
2.2 kB
Part 17-Module 01-Lesson 14_Regression/04. Introduction to Linear Regression-RD4zbBvXDnM.pt-BR.vtt
2.2 kB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/31. Small Multiples And Dual Axis-bx6MxsoDqsI.en.vtt
2.2 kB
Part 09-Module 01-Lesson 01_What is EDA/02. Go Exploring-dias-YUpewk.ja.vtt
2.2 kB
Part 12-Module 02-Lesson 08_Technical Interview - Python/01. Interview Introduction-dRsHYt1Lddc.zh-CN.vtt
2.2 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-f7vNKm0Zci0.en.vtt
2.2 kB
Part 21-Module 01-Lesson 05_Scripting/02. Python Installation-2_P05aYChqQ.pt-BR.vtt
2.2 kB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/05. Investigation Process-5o2x4UsumLY.zh-CN.vtt
2.2 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/06. Words of Wisdom from Zipfian Academy-ani9_ZalK-8.zh-CN.vtt
2.2 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/24. Drawing Circles-GlIXt29deCA.zh-CN.vtt
2.2 kB
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.ar.vtt
2.2 kB
Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-OB7iJnEY0Tg.zh-CN.vtt
2.2 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-FpcCdcKFBKM.pt-BR.vtt
2.2 kB
Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-1Hd1Bq1YxXg.pt-BR.vtt
2.2 kB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.en.vtt
2.2 kB
Part 12-Module 01-Lesson 03_Interview Fails/02. Interviewing Fails Mike Wales-OGXRmzBglI4.pt-BR.vtt
2.2 kB
Part 12-Module 02-Lesson 03_Searching and Sorting/01. Binary Search-0VN5iwEyq4c.zh-CN.vtt
2.2 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/19. Pooled Standard Error-iub8yWiO84I.en.vtt
2.2 kB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.it.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/02. Fitting Logistic Regression-Dg0rBDQnIYg.zh-CN.vtt
2.2 kB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby-aWc18hHpXRk.en.vtt
2.2 kB
Part 05-Module 02-Lesson 05_Deeper into SQL/02. Normalized Design Part One-LQq5F77ANiY.pt-BR.vtt
2.2 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.en-US.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-IMWsjjIeOrY.ja.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-lWjaCJazJE0.en.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/06. Subqueries Part II-jko-RrZd0R8.ar.vtt
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Part 12-Module 01-Lesson 02_Practice Behavioral Questions/07. What Do You Know About the Company-CcTfHemUvbM.zh-CN.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/15. LIMIT Statement-cCPHNNhBgpQ.pt-BR.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/18. ORDER BY Statement-wqj2As31LqI.pt-BR.vtt
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Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-KYAUEz-50-Q.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-KYAUEz-50-Q.es.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/16. Measure Variability-g_V6OCICUUc.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/48. Adding the Axes to the Page-B3qrRUamyUs.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/06. DF - Marginal Totals-PBcd_dxiFbE.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-DclTt9xqS4s.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/14. -z-mXs7Rl-Ys.en-US.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/25. Sorting the Data for Drawing Order-X-zVfcuacD4.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-tfhsgVCX2Ao.en.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/01. Intro to MongoDB-GfK7GW3V-W0.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.zh-CN.vtt
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Part 12-Module 02-Lesson 05_Trees/18. Self-Balancing Trees-EHI548K3jiw.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.es-ES.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/26. Predicting Based on Many Features-oZqGlJbRZu4.zh-CN.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.es-MX.vtt
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.es-MX.vtt
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.es-MX.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/14. -z-mXs7Rl-Ys.en.vtt
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Part 17-Module 01-Lesson 14_Regression/15. Fitting A Regression Line In Python-0CiMDbEUeS4.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -Vf-EK6vg6Uc.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/18. Author-driven Examples-mr2HGcqk3nU.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/32. What Happened-NSuT87J4V-g.en.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/05. Resume Reflection-8Cj_tCp8mls.zh-CN.vtt
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection-8Cj_tCp8mls.zh-CN.vtt
2.2 kB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection-8Cj_tCp8mls.zh-CN.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/01. Introduction -rkRn1Nh-6lg.pt-BR.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess-XoQr2hohdvI.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-EtWewV65zbs.zh-CN.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ivBGyL3SzO0.zh-CN.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Solution --faitcQ7SKs.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/01. Welcome!-KJT4Z0xpHns.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-Fkm7ogOussQ.ar.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-lWjaCJazJE0.pt-BR.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/27. L2 04 Tuples V3-33xN-AbTMoc.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/31. Dependent Samples-kcTh3hJ1XCw.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/38. Naive Bayes Mini-Project Video-UH2oSijkszo.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.it.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection-S-xe0-XNo4I.ar.vtt
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Part 19-Module 01-Lesson 02_Design/02. Lesson Overview-Gg77PqkQkhs.ar.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/38. Something Fun-7kOZs5PLtqs.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/06. Critical Regions-UF3japjNx98.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/03. Types in the SQL World-8swA-PqlEP0.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/08. Scraping Webpages -bAeGbBBAIkE.zh-CN.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.en.vtt
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Part 21-Module 01-Lesson 03_Control Flow/07. Truth Value Testing-e52uw7ejV8k.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/22. Scraping Solution-J1gn4ZBLkt4.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-1Hd1Bq1YxXg.en.vtt
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Part 11-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.en.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-XqEQG4qo94I.ar.vtt
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Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-NvgWKf-iBsw.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/08. Unemployment Line Plot-EbD9ufptNd0.ar.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/30. Arithmetic Operators-fgcJdiNECxI.pt-BR.vtt
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Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-t2Nq3MFK_pg.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/10. Estimating Click-Through-Probability-Hkbc_vcb7D8.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-S1yjJWWza7g.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/23. Measures of Center-eNoE9hSDxPA.ar.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/12. Projection Queries-dFGlIC9nI1Q.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/34. From Source Code to Graphic-PIqgFTee-lk.zh-CN.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/01. Introduction to Data Visualization-MUZXLvBI2sw.ar.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/01. Introduction to Data Visualization-MUZXLvBI2sw.ar.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/05. A Simple HTTP Server-h8Fa24E_I5s.pt-BR.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/08. Self JOINs-tw_VzEGBOvI.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/01. Summary-51hx5u2EMZA.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.zh-CN.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/12. Which Distribution-tTb1k27rhgI.pt-BR.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Data in the Real World-HmipezTjTDY.ar.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.zh-CN.vtt
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.zh-CN.vtt
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.zh-CN.vtt
2.1 kB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. Assignment Operators-p_qfzL-x3Cs.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.pt-BR.vtt
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Part 12-Module 01-Lesson 03_Interview Fails/02. Interviewing Fails Mike Wales-OGXRmzBglI4.es-MX.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/01. What is Data Visualization-mfLklbVU7r0.zh-CN.vtt
2.1 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/23. Keeping Trust and Drawing Circles-pBLeU5bbKak.zh-CN.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/05. Confidence Interval for a Difference In Means-8hrWGzjyhck.pt-BR.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces)-1y_qjUMDsCw.ar.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/12. Which Distribution-tTb1k27rhgI.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.ja.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.ar.vtt
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Part 11-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm-hGKY6BAqJ6o.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/39. Update the Title-ut83yNUYLmc.pt-BR.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/21. Order By Part II-XQCjREdOqwE.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-2ieszOqnpWs.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/03. Unit of Diversion Example-_-BxFJTBNMM.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/04. XML in Practice-4xsz7OkDJgM.pt-BR.vtt
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/07. Format-Xlqoq-SoJso.en.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2-Vvzl2J5K7-Y.zh-CN.vtt
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Part 12-Module 01-Lesson 02_Practice Behavioral Questions/04. Time When You Showed Initiative-29mkriaGT0E.en.vtt
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Part 12-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-R9AtVBq2Z5E.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-QJxhBCWK6BQ.pt-BR.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/14. Multiple Metrics Example 2-m0E26ndQBNo.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/20. Building the Linear Model-zyIc0sXYk2A.pt-BR.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-WnQoZzxas-g.zh-CN.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/03. Setting Up Hypotheses - Part I-NpZxJg4S6X4.zh-CN.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations-q5PjL9GkVtM.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.ja.vtt
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Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-E63RZli2F2o.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/47. Creating Axes-3jEbyeW1Re4.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations-q5PjL9GkVtM.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.en-US.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python-KS6cKoKe8ms.pt-BR.vtt
2.1 kB
Part 03-Module 01-Lesson 11_L4 Variability/34. Spreadsheet SD-sXeVydVAv7Q.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/01. Welcome!-KJT4Z0xpHns.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/23. Changing the Date Format-_jOLSNoKxhQ.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/21. Storing Data-hcosH34b-yw.ar.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/03. Good GitHub repository-qBi8Q1EJdfQ.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.en.vtt
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Part 11-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.en.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/01. Introduction-Z8WNfx9Oq9s.ar.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/12. Final Tips-1ZVBvM54hQw.en.vtt
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Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-iCTPBcowJRY.ar.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Introduction to Summary Statistics-PCZmHCrcMcw.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.en.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-WCcnGQY771c.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-WCcnGQY771c.pt-BR.vtt
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Part 05-Module 01-Lesson 05_Data Quality/09. Auditing Validity-B9vjn8IYaSg.zh-CN.vtt
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Part 12-Module 02-Lesson 05_Trees/08. Search and Delete-KbL-HK3ztX8.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-zovzbp_Rpu4.en-US.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/06. Interpreting Results-UPOxxbKu6CQ.en.vtt
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.en.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question-XvvKBmKC_84.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/17. Inspecting the X-axis-huZPg2gRmLk.pt-BR.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-eZ_yCrh4740.ar.vtt
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby-aWc18hHpXRk.zh-CN.vtt
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Part 11-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.zh-CN.vtt
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Part 12-Module 02-Lesson 02_List-Based Collections/05. Linked Lists-zxkpZrozDUk.en-US.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/06. Why Businesses Choose Databases-j4ey7--h9r8.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/22. Why Businesses Choose Databases-j4ey7--h9r8.zh-CN.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/01. Intro to SQL for Data Analysis-CU4igXr9xTw.en-US.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/06. Quick Fixes-Lb9e2KemR6I.pt-BR.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-zovzbp_Rpu4.en.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/03. Choosing Invariants-qCnbDgy2yHk.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/01. Intro to SQL for Data Analysis-CU4igXr9xTw.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-t0iflCpBUDA.ja.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/03. Your First JOIN-HkX9fkNRbU8.en.vtt
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/05. Cleaning With More Advanced String Functions-E6cK8RbYGEc.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-P8ZxaAQTZXQ.en.vtt
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Part 12-Module 02-Lesson 02_List-Based Collections/05. Linked Lists-zxkpZrozDUk.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Solution --faitcQ7SKs.zh-CN.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-80aFO4KmcPM.zh-CN.vtt
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Part 21-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/28. Assumptions-CdoWdNAKSYw.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/18. Author-driven Examples-mr2HGcqk3nU.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-KYAUEz-50-Q.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-KYAUEz-50-Q.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-WZRsqdNrC1A.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.ar.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/40. Jelly Beans-1HmiArFN-EI.ar.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-lVLgiRRhFpQ.en.vtt
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Part 12-Module 02-Lesson 06_Graphs/11. BFS-pol4kGNlvJA.zh-CN.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-KYa8_fuZ30w.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-lVLgiRRhFpQ.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/16. Advice for Data Scientists-FdkhUOtHIFg.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-095MTpItufM.ar.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/24. WHERE Statements -mN0uTnlXaxg.zh-CN.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Notation for the Mean-3EF15AoRxyM.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.th.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/16. Pandas groupby()-w3D0no7E8uw.en.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/16. Pandas groupby()-w3D0no7E8uw.en.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/08. Dummy Variables--QTgDd-fZuA.en.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/01. Introduction-XtJN72lBo94.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.ar.vtt
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Part 12-Module 02-Lesson 02_List-Based Collections/09. Stacks Details-HpaVHzDeZC4.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/50. Grammar of Graphics and D3 Functions-rADl_md-WNM.ar.vtt
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Part 11-Module 01-Lesson 08_Outliers/08. Outliers Mini-Project Video-GRN0Whyy4Lk.ar.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/08. Features != Information-GOrv8faKHV4.ar.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/08. Scraping Webpages -bAeGbBBAIkE.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/14. The Central Limit Theorem-ag3TB5UGu_g.en.vtt
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Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-OGK9SHt8SWg.en.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/06. Choosing Metrics-mOH45PzylKk.zh-CN.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/12. One-Sample t-Test-QyjjSIvJ_F4.en.vtt
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/01. Intro-vek87HVWexE.zh-CN.vtt
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/01. Intro-vek87HVWexE.zh-CN.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/02. Sets and Maps-gmIb-qZhTDQ.zh-CN.vtt
2.1 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/17. Collecting Stadium Locations-CqE3Zqv21Wo.zh-CN.vtt
2.1 kB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/18. 39. SAD-tya_avP-hKc.zh-CN.vtt
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Part 09-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-t_ZSrov187k.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-n0lluEhKUfQ.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-VUfaXWrr3oY.ja.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-UNqgFhKvCL4.ar.vtt
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Part 21-Module 01-Lesson 05_Scripting/13. Handling Error Specifying Exceptions-EHW5I7shdJg.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/13. Tracking Down the Remaining Problems-Xblj5rT9i0M.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer-SsNYXdi3q-I.ja.vtt
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/14. COALESCE-86vgu-ECBCQ.ar.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/43. AND BETWEEN Operators-nBuDPneWcKY.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.ar.vtt
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Part 09-Module 01-Lesson 01_What is EDA/07. Our Approach for This Course-dBsf-szQ00s.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-P8ZxaAQTZXQ.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/20. Building the Linear Model-zyIc0sXYk2A.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/22. Decomposing Visualizations-iJ8t2FsPW4c.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-hUmXWHOPxpI.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/13. Thematic Maps-Jw2q-B2kM9k.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/29. Decision Errors-4QMqg8izUac.pt-BR.vtt
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Part 19-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings-98aog0eVcC4.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots-llvIDIu3Sw8.en.vtt
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Part 12-Module 01-Lesson 03_Interview Fails/02. Interviewing Fails Mike Wales-OGXRmzBglI4.en.vtt
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Part 11-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-FpcCdcKFBKM.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-pn3MunHovMc.pt-BR.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/14. Multiple Metrics Example 2-m0E26ndQBNo.en.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/04. Further Motivation-sjGxUKrbKoI.ar.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/11. How Do I Find Time for My Nanodegree Program-d-VfUw7wNEQ.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/13. One-Sample t-Test-IdP9Ps2tHgw.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data-D7m25cvqUpw.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-B_fHrMIzIgE.ja.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/14. JOINs-CxuHtd1Daqk.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/32. What Happened-vD9iXeq3PKc.pt-BR.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather Intro-K5ITQn1L1R0.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/16. Subqueries-YWZ-bgnZWaM.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.ja.vtt
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Part 13-Module 01-Lesson 04_Design Principles/03. Parts of Speech Analogy for Data Vis-bO8clma7Mnc.en.vtt
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Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules Part II-aASigWQ_XU0.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-mZgPfxFOFRE.ar.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-oZkDSuhBEkE.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/19. Checking the Nest Return-hCXhsYVLqig.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/15. Different Bin Sizes-_wOXWBZkL58.es.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/21. Best Practices for Scraping-97FYi0SQFQ8.ar.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/11. Z-Table-hSAxcGBxbds.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance-QReeBef_7vM.ar.vtt
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Part 17-Module 01-Lesson 14_Regression/02. Introduction to Machine Learning-pLcFPPI1L-0.en.vtt
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Part 17-Module 01-Lesson 14_Regression/15. Fitting A Regression Line In Python-0CiMDbEUeS4.en.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-C6okqt-jf08.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-YPPQy_eB2mU.zh-CN.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/12. Iterating on Visualizations-muh0thR2DKo.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-C6okqt-jf08.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.ja.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-DclTt9xqS4s.en.vtt
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Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-CvTXyvw7QLc.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/15. SD of Karma Points per Post-uCRzrlaA8mg.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-plnMY4iATyU.pt-BR.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/13. Multiple Metrics Example-0eCWo0h5DpM.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/30. R Squared Metric for Regression-yDJEP-XSWdU.pt-BR.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question-XvvKBmKC_84.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/13. Explanatory vs Exploratory-SHq_zbB4ITo.ar.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/17. -NXGcCf1KCt4.en-US.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.pt-BR.vtt
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Part 09-Module 01-Lesson 01_What is EDA/02. Go Exploring-dias-YUpewk.en.vtt
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Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-hxxa0KAkB1o.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/16. -_mge9UU-gpQ.en-US.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/31. Small Multiples And Dual Axis-bx6MxsoDqsI.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/10. 95 CI with Exact Z-Scores-apqUAtnsLZE.zh-CN.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.pt-BR.vtt
2.1 kB
Part 11-Module 01-Lesson 12_Feature Selection/02. A New Enron Feature-m2-LkgEfLO0.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/21. Rankings of Visual Encodings-ycsXqX7T80Y.en.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-tGHQsk1SGGU.pt-BR.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/08. Rankings of Visual Encodings - Data Visualization and D3.js-ycsXqX7T80Y.en.vtt
2.1 kB
Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-GUD6yl0A1Aw.ar.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.en.vtt
2.1 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/17. -NXGcCf1KCt4.en.vtt
2.1 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/25. Sorting the Data for Drawing Order-X-zVfcuacD4.pt-BR.vtt
2.1 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/29. Formula for Location of Median-h3zyZHNyreM.en.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/16. -_mge9UU-gpQ.en.vtt
2.1 kB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.ja.vtt
2.1 kB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/02. What's Ahead-ggbCydfI1JM.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.ja.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/17. Inspecting the X-axis-huZPg2gRmLk.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.ar.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/24. Are your Results Just Noise-LjuF5M6ymPA.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.zh-CN.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/28. Conclusion-rrSNkPGJmTc.ar.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-_7Vqou7k7fI.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-VUfaXWrr3oY.pt-BR.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/22. Variability Example-kTXI_wnTbVk.pt-BR.vtt
2.1 kB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.es-ES.vtt
2.1 kB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/22. Bootstrapping-42j3YclcZ4Q.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces--VxKwVvrNY0.zh-CN.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example-Ae_UOATWmDM.pt-BR.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces--VxKwVvrNY0.zh-CN.vtt
2.1 kB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-XDvus8zHJbA.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/30. R Squared Metric for Regression-yDJEP-XSWdU.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-CuMPjPESfY0.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.zh-CN.vtt
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Part 12-Module 02-Lesson 03_Searching and Sorting/01. Binary Search-0VN5iwEyq4c.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -oWu4UDkPmj8.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.ja.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/40. NOT Operator-dSQF87oW8a0.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.ar.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/11. How Do I Find Time for My Nanodegree Program-d-VfUw7wNEQ.en-US.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/27. Bar Chart The Bad-FCapLzYUQSo.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-CvTXyvw7QLc.pt-BR.vtt
2.1 kB
Part 13-Module 01-Lesson 05_Dimple.js/11. Chart Layout and Group Tags--2yj49s7v5w.en-US.vtt
2.1 kB
Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-IMWsjjIeOrY.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/09. -zWNcZ-7k7Tw.zh-CN.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/08. Dummy Variables--QTgDd-fZuA.pt-BR.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/11. How Do I Find Time for My Nanodegree Program-d-VfUw7wNEQ.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/13. Tracking Down the Remaining Problems-Xblj5rT9i0M.en.vtt
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Part 11-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm-hGKY6BAqJ6o.en.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye-sJgPnuiHrs8.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/11. Chart Layout and Group Tags--2yj49s7v5w.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.zh-CN.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/19. What is Notation-MaHV5cKfcmE.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.th.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/01. Introduction-4U3nFMf2KEs.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/28. Improving Plots and Sharing Findings-anglRHbmsfw.zh-CN.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/24. all Operator-B3iYl-2HSXI.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/30. Thinking with Venn Diagrams-C1aHeMSeIdk.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/44. Parsing Overview and Parsing Attendance-_tVC3JuW7to.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.ar.vtt
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Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Using With-OQ-Y0mMjm00.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/28. Probability of Obtaining Mean-ErwocwQVgYE.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/41. Types of Designs-IcrYt7Tzccg.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.en.vtt
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Part 17-Module 01-Lesson 04_Probability/19. Probability Conclusion-dsVKoXymYDU.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.es.vtt
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Part 12-Module 02-Lesson 05_Trees/08. Search and Delete-KbL-HK3ztX8.pt-BR.vtt
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Part 11-Module 01-Lesson 16_Tying It All Together/04. Outro-VCNcNnZ6V_s.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-pX849ta6kaI.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/22. Variability Example-kTXI_wnTbVk.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-9piyE5in7YE.es.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/01. Welcome!-KJT4Z0xpHns.ja.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.en.vtt
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Part 12-Module 02-Lesson 02_List-Based Collections/09. Stacks Details-HpaVHzDeZC4.zh-CN.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Data Types-gT6EYlsLZkE.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.it.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/18. Multicollinearity VIFs-uiF3UcDWwPI.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/28. Outlining the Update Function-k5ZZQ3ulwX4.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/29. Correcting Color-7vaHp4caWxw.pt-BR.vtt
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.es-MX.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Notation Parameters vs. Statistics-webref_dLrA.ar.vtt
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.zh-CN.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/04. Introduction to Hashing-8yik3RlDFgM.en-US.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-pn3MunHovMc.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.zh-CN.vtt
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Part 12-Module 02-Lesson 05_Trees/02. Tree Basics-oaxLPzaXRDc.en-US.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/16. Beginning to Build Our http Requests-ojd7xXOd_64.pt-BR.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/24. Conclusions In Hypothesis Testing-I0Mo7hcxahY.pt-BR.vtt
2.0 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-8HFOaRdDpek.pt-BR.vtt
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/02. Purpose-7F7cMCTcyhM.en.vtt
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Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8xFV-I4VqZ0.pt-BR.vtt
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Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-t2Nq3MFK_pg.pt-BR.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/04. Introduction to Hashing-8yik3RlDFgM.en.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/01. Interview Introduction-dRsHYt1Lddc.pt-BR.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/07. Types Of Errors - Part I-aw6GMxIvENc.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-8HFOaRdDpek.pt-BR.vtt
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Part 12-Module 02-Lesson 05_Trees/02. Tree Basics-oaxLPzaXRDc.en.vtt
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Part 17-Module 01-Lesson 13_Case Study AB tests/04. Business Example-Wzz7omSDfEk.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-T_LpzJl-EVE.ar.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.en-US.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/01. Intro-8y2JZ2gEl1k.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/01. Intro-jOhaqX_9oy8.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation-Mak839YmmrA.ar.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-P1aYwQhPnPQ.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/03. Developer Tools and Console-C2Ob9vkpQ7g.zh-CN.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/05. COUNT NULLs-ngxgqfFFFLQ.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.pt-BR.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/05. Resume Reflection-8Cj_tCp8mls.pt-BR.vtt
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection-8Cj_tCp8mls.pt-BR.vtt
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection-8Cj_tCp8mls.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-7lKhG9bIMhs.ar.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/11. Chart Layout and Group Tags--2yj49s7v5w.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-0XM5ILuCg1k.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.ar.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/03. Data Types and NULLs-RgTcYwKqtYI.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.zh-CN.vtt
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Part 12-Module 02-Lesson 05_Trees/02. Tree Basics-oaxLPzaXRDc.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/16. Measure Variability-g_V6OCICUUc.zh-CN.vtt
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Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-hxxa0KAkB1o.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.ja.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.es-ES.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/18. Averaging Locations-GLQJukg-0fQ.pt-BR.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-vuu3BY7X9ps.zh-CN.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/12. Plot Colors for Qualitative Factors-2ZVGl6LrOPw.ar.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/22. Decomposing Visualizations-iJ8t2FsPW4c.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/06. Dimple Bar Chart Code Overview-vuxN6EC_gso.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/30. Thinking with Venn Diagrams-C1aHeMSeIdk.en.vtt
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Part 17-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.ar.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/24. Conclusions In Hypothesis Testing-I0Mo7hcxahY.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-plnMY4iATyU.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/15. Roll 1 Die-oJXYNArEk8k.pt-BR.vtt
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Part 12-Module 02-Lesson 06_Graphs/07. Adjacency Matrices-FsFhoTALA1c.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-GtR3dw2eq2w.zh-CN.vtt
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/02. Purpose-7F7cMCTcyhM.pt-BR.vtt
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/02. Purpose-7F7cMCTcyhM.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-VBs6D4ggnYY.ar.vtt
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Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/18. Combining Pandas DataFrames-vB_Et1hz_2M.zh-CN.vtt
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/07. Format-Xlqoq-SoJso.zh-CN.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/35. Visualization and D3 Basics-ueKb1OghNEU.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel-j5tA__Dq-sQ.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/18. Combining Pandas DataFrames-vB_Et1hz_2M.zh-CN.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/09. Types Of Statements-vLvJbIz94C4.ar.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/22. Types Of Statements-vLvJbIz94C4.ar.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Ilu1JjjAbwA.ar.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/23. Connecting Errors and P-Values-hFNjd5l9CLs.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/15. Getting Data from First Week -iT1vtUy2utg.ar.vtt
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Part 11-Module 01-Lesson 13_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/19. Engagement Ratio-vpwCy5Gphrw.en-US.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/01. Introduction-0ydaJl3wCkU.pt-BR.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-Nmf80xB1DN0.ar.vtt
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Part 17-Module 01-Lesson 14_Regression/08. Correlation Coefficients-rL5Bn8Fi-zE.pt-BR.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/11. Correlation Coefficients-rL5Bn8Fi-zE.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/19. Engagement Ratio-vpwCy5Gphrw.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/12. What's a DB-API-06LsRU4pmkA.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/20. Hypothesis Testing Song-ER5AITzr77g.pt-BR.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-t_ZSrov187k.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-QJxhBCWK6BQ.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/27. Klout Parameters-wV-6gQepmn0.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/23. CI Bounds-T9VX2KvzJ-k.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-XUZIGbX3JIg.ja.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/64. All World Cup Games Recap-tVtEEL5i_BE.zh-CN.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/27. Empirical Variability Bootstrapping-FvtAeWdzy4k.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/16. Beginning to Build Our http Requests-ojd7xXOd_64.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-lbNk216NW48.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-lbNk216NW48.ar.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-cgWAzXtglF0.zh-CN.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/06. Ethical Considerations for Diversion-Zf0XzYNsado.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/38. Something Fun-7kOZs5PLtqs.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.en.vtt
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Part 09-Module 01-Lesson 01_What is EDA/02. Go Exploring-dias-YUpewk.pt-BR.vtt
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Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-wl3gjMMrYwM.pt-BR.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/06. Ethical Considerations for Diversion-Zf0XzYNsado.pt-BR.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/34. LIKE Operator-O5z6eWkNip4.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.es-ES.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/26. Where are we-d3jQdOuOy8k.zh-CN.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/05. Resume Reflection-8Cj_tCp8mls.es-MX.vtt
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection-8Cj_tCp8mls.es-MX.vtt
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection-8Cj_tCp8mls.es-MX.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-WkInrWZwbNA.zh-CN.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Common Table Expressions-qtEKO7B8bXQ.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/27. Empirical Variability Bootstrapping-FvtAeWdzy4k.en.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/12. Multiple Metrics Introduction-dw0UylGwPe8.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-WCcnGQY771c.en.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-bcwFahJsww0.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/14. Common and Less Common Charts on plot.ly-V9xxdiwJtWk.zh-CN.vtt
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Part 15-Module 01-Lesson 02_Design Principles/06. Gráficos Comuns e Menos Comuns no plot.ly-V9xxdiwJtWk.zh-CN.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/16. Performance Tuning 2-arMtEhSoq7E.en.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-WCcnGQY771c.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/27. Results from Sample-ypIyvJyZAs8.ko.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.zh-CN.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-kWsDkFkEjNM.ar.vtt
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Part 09-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-OzPNbN4L_L0.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/08. t-Table-lccjSiVTx7c.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/16. Pandas Series apply()-lhcl1UjM_0Q.ar.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling And EDA-EQXfxbUup0o.ar.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/17. Pandas Series apply()-lhcl1UjM_0Q.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.es.vtt
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Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.zh-CN.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.th.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-ncFtwW5urHk.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.en.vtt
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Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-djTM5fADIVs.en.vtt
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Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-XZNKM3xMZNY.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-9piyE5in7YE.en.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/08. Infinitely Small-9ftDJRsfEUI.pt-BR.vtt
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Part 21-Module 01-Lesson 05_Scripting/13. Handling Error Specifying Exceptions-EHW5I7shdJg.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/04. Features and Labels Musical Example-rnv0-lG9yKU.ja.vtt
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Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-IwcoGtFuYSo.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/34. Spreadsheet SD-sXeVydVAv7Q.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-DclTt9xqS4s.ja.vtt
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Part 13-Module 01-Lesson 04_Design Principles/40. Lie Factor-jkR2kIJrvBM.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/01. Introduction-XtJN72lBo94.en.vtt
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Part 05-Module 01-Lesson 05_Data Quality/02. What is Data Cleaning-dzqOwmxK3j4.ar.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/01. Intro to MongoDB-GfK7GW3V-W0.zh-CN.vtt
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.pt-BR.vtt
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/20. Negative Space-3toURbAUt9s.ar.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/05. A Simple HTTP Server-h8Fa24E_I5s.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.es.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-NRCs22HJ-vI.ar.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-8oM8KjsntG8.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-TSw2AAaKxBA.pt-BR.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/01. Instructor Introduction Juno Lee-to8Pp3PCOZo.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/07. Loading Data into a DataFrame-N66_j0gxuhg.ar.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-LlPsmQx5y50.zh-CN.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/18. ORDER BY Statement-wqj2As31LqI.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.en-GB.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate-eu1gO_76pSY.ar.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/07. Loading Data into a DataFrame-N66_j0gxuhg.ar.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/02. Normalized Design Part One-LQq5F77ANiY.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.ja.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/02. A New Enron Feature-m2-LkgEfLO0.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/27. Results from Sample-ypIyvJyZAs8.es-ES.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/22. NEW D3 Scale Syntax-ba-Luz-Ip0Y.en-US.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-QII0tSAIex0.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-Hb2q-o4ElV4.ko.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-eAKVYAR_VlY.zh-CN.vtt
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Part 12-Module 02-Lesson 02_List-Based Collections/05. Linked Lists-zxkpZrozDUk.zh-CN.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/22. NEW D3 Scale Syntax-ba-Luz-Ip0Y.en.vtt
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Part 19-Module 01-Lesson 02_Design/07. Chart Junk-3BTBEYOG2o8.zh-CN.vtt
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Part 21-Module 01-Lesson 04_Functions/11. L4 08 Lambda Expressions V3-wkEmPz1peJM.zh-CN.vtt
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Part 11-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy-b-oE175NJiQ.ar.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-kT0jBsXOouw.ar.vtt
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Part 09-Module 01-Lesson 01_What is EDA/04. Aude's Interest in Data-DDNSMG_RltY.en.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-j0qfuunqym8.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-O0zo3-NtBSI.zh-CN.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/17. -NXGcCf1KCt4.zh-CN.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.en.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess-XoQr2hohdvI.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.en.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-lVLgiRRhFpQ.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/35. Point of SD-d-_ZKyocTDw.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/15. Bigger Sample, Smaller CI-DRarpjC23kc.pt-BR.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-rGw4xFsUUqE.ar.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/21. Working with Outliers-4RnQjtJB8t8.zh-CN.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/06. Subqueries Part II-jko-RrZd0R8.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.en.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/28. Multiple Testing Corrections-DuMgeHrkIF0.zh-CN.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/25. L2 05 Lists Methods V1-WXkPm4rv6ng.zh-CN.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/09. Querying Using Field Selection-V2UMNT9VBrw.ar.vtt
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Part 15-Module 01-Lesson 02_Design Principles/16. Gráfico Lixo-jm2qOX2Q2HQ.zh-CN.vtt
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Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-wl3gjMMrYwM.en.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/12. Final Tips-1ZVBvM54hQw.pt-BR.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators-48AgxPygRuQ.zh-CN.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/13. Motivation for Other JOINs-3qdv1Ojc9Og.en.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score-6kdmc3iTf78.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/20. Hypothesis Testing Song-ER5AITzr77g.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/52. The Purpose of the Grammar of Graphics-pZyrfzuB5FE.ar.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/06. DF - Marginal Totals-PBcd_dxiFbE.en.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/01. Introduction to Data Visualization-MUZXLvBI2sw.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.ja.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.zh-CN.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-q46nO0mznXM.ja.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/12. Final Tips-1ZVBvM54hQw.zh-CN.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/09. Scatter Plots -DvlxZ37O4i8.zh-CN.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-7HMAtB-342I.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/09. Chart Suggestions-5V109AVr_JE.ar.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/22. Bootstrapping-42j3YclcZ4Q.en.vtt
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Part 12-Module 01-Lesson 03_Interview Fails/02. Interviewing Fails Mike Wales-OGXRmzBglI4.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/29. Correcting Color-7vaHp4caWxw.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-WGD8AWQg9dE.zh-CN.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/30. Arithmetic Operators-fgcJdiNECxI.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/15. One Human Heartbeat-unKu-dmor2w.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/39. Update the Title-ut83yNUYLmc.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/32. What Happened-vD9iXeq3PKc.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-WZRsqdNrC1A.zh-CN.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/04. XML in Practice-4xsz7OkDJgM.zh-CN.vtt
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Part 11-Module 01-Lesson 01_Welcome to Machine Learning/03. Introduction Pt. III-0ZuxGhiqo5U.ar.vtt
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Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-rNR4_JqCEuk.ar.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-oZkDSuhBEkE.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bgyN3RO2ICo.ar.vtt
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/16. Comparing Row to Previous Row-Z_x5ZJyDZog.pt-BR.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bgyN3RO2ICo.ar.vtt
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Part 19-Module 01-Lesson 02_Design/18. Tell A Story-_IdOUEhjVGI.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts-q-EjlMl1Bj4.ar.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-MV_e0z9kFjM.pt-BR.vtt
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Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-HSeIrqW-YGw.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/01. Introduction to Conditional Probability-Ok8948Wcbmo.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/05. The Difficulty of Data Visualization-xzo96P5BwSI.en.vtt
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Part 11-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites-0ANDJ8i_deE.ja.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/12. What's a DB-API-06LsRU4pmkA.en.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/06. Quick Fixes-Lb9e2KemR6I.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-sLEF-B1fkX8.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/08. Map Distortions-xL5xVEuLuNE.zh-CN.vtt
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/08. Hierarchies with Trina-ys8Cn0o5gNI.en.vtt
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/03. Hierarchies with Trina-ys8Cn0o5gNI.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-KYAUEz-50-Q.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-KYAUEz-50-Q.zh-CN.vtt
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Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-djTM5fADIVs.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.it.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/46. OR Operator-3vLGEuXAAvA.zh-CN.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/29. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-zlopUR9utUY.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-jKZAcZw9xLA.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.zh-CN.vtt
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Part 11-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning-Xcb9jjjAm60.ar.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Data Types-gT6EYlsLZkE.en.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-zlopUR9utUY.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/15. Different Bin Sizes-_wOXWBZkL58.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/22. Comparing the Two Student Groups-eM82u21V7AM.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-MEtIAGKweXU.en.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/18. Recreating China's Red Dot-tDRHSTivs4k.en-US.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/04. Iterative Process-m2qDeWrGIDI.pt-BR.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-j0qfuunqym8.zh-CN.vtt
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Part 19-Module 01-Lesson 02_Design/19. Same Data Different Stories-jSSnkz3QT5Y.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-jfGdUdo37Vk.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data-vhl-SADfti8.pt-BR.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/11. How Do I Find Time for My Nanodegree Program-d-VfUw7wNEQ.zh-CN.vtt
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Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-HyjBus7S2gY.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.bg.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/18. Recreating China's Red Dot-tDRHSTivs4k.en.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/14. Anscombe’s Quartet-Ftp3mmItV-k.en.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Anscombe’s Quartet-Ftp3mmItV-k.en.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/05. COUNT NULLs-ngxgqfFFFLQ.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/29. Decision Errors-4QMqg8izUac.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/35. Summary of the Update Function-IVmBlMgErzY.en.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/04. Describe Your Work Experiences-B1LED4txinI.pt-BR.vtt
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/04. Describe Your Work Experiences-B1LED4txinI.pt-BR.vtt
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences-B1LED4txinI.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.ja.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.ja.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/04. More Examples-gj-or8b8TmM.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/25. Margin of Error-slBW5Neh2cs.pt-BR.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-zovzbp_Rpu4.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-MEtIAGKweXU.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/05. The Difficulty of Data Visualization-xzo96P5BwSI.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.es-ES.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-8_SBvU8NYak.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-8_SBvU8NYak.es.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.zh-CN.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Subqueries Using WITH-IszTmDKyKHI.ar.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-sLEF-B1fkX8.en.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/15. Experiment Design and Sizing Overview-6_odiPIKZO0.ar.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions-EvhIgrXtOao.en.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.ar.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/12. One-Sample t-Test-QyjjSIvJ_F4.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/08. Darts-fSj1dwh7Kxc.pt-BR.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video-sJzKx_FiMXA.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.th.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/21. Sampling Observations-PsRMReOqccg.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/12. Affect t-Statistic-c6vE21UVksU.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/16. Pandas groupby()-w3D0no7E8uw.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/16. Pandas groupby()-w3D0no7E8uw.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/19. Engagement Ratio-EdIcXVIYX88.en.vtt
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Part 09-Module 01-Lesson 01_What is EDA/02. Go Exploring-dias-YUpewk.zh-CN.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/01. Introduction-4U3nFMf2KEs.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/19. Engagement Ratio-vpwCy5Gphrw.zh-CN.vtt
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Part 12-Module 02-Lesson 02_List-Based Collections/02. Lists-KUQSgUMtyv0.en-US.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-xPZOSx1q_dg.ar.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip Solution -Pzy8nHA_EJc.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/15. Why Even Create Graphics-lqI3LFwMVUc.ar.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Why Even Create Graphics - Data Visualization and D3.js-lqI3LFwMVUc.ar.vtt
1.9 kB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Statement-DRmkKVhe6-s.pt-BR.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/01. Introduction-4U3nFMf2KEs.zh-CN.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/01. Intro to SQL for Data Analysis-CU4igXr9xTw.zh-CN.vtt
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/07. Format-Xlqoq-SoJso.es-MX.vtt
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Part 11-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.zh-CN.vtt
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Part 12-Module 02-Lesson 02_List-Based Collections/02. Lists-KUQSgUMtyv0.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/03. Types of Effect-Size Measures-FWSS2VadyBg.en.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/03. What is the Difference-I3tQvrCgNrQ.ar.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-X_AS8NBngsk.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/27. Communication-P36LwI-R2Vw.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.pt-BR.vtt
1.9 kB
Part 11-Module 01-Lesson 15_Evaluation Metrics/01. Welcome to Evaluation Metrics Lesson-IHuFWRM9f9Q.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/40. Creating Time and Attendance Scales-PgAp8ob4hIM.en.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score-6kdmc3iTf78.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/06. Dimple Bar Chart Code Overview-vuxN6EC_gso.en.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.zh-Hans.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.zh-Hans.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/21. Be Happy and Get Rid of Negatives-_afLozDIcLw.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/08. t-Table-lccjSiVTx7c.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/27. Results from Sample-ypIyvJyZAs8.pt-BR.vtt
1.9 kB
Part 17-Module 01-Lesson 11_Confidence Intervals/02. Sampling To Distributions To Confidence Intervals-QYMLkDToigc.zh-CN.vtt
1.9 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-QX_KFUXtHkw.ar.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-wqvEtUA0n-s.pt-BR.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video-sJzKx_FiMXA.en.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/21. Order By Part II-XQCjREdOqwE.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-QX_KFUXtHkw.ar.vtt
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Part 19-Module 01-Lesson 02_Design/19. Same Data Different Stories-jSSnkz3QT5Y.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/07. Anatomy of a Table-PhvA7DCgtpw.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.ja.vtt
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Part 12-Module 02-Lesson 05_Trees/16. Heapify-CAbDbiCfERY.en-US.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/19. Adding the Series and Drawing the Chart-2zcZXJzW0aw.ar.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/15. LIMIT Statement-cCPHNNhBgpQ.en.vtt
1.9 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-TSw2AAaKxBA.en.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-8HFOaRdDpek.en.vtt
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Part 09-Module 01-Lesson 01_What is EDA/04. Aude's Interest in Data-DDNSMG_RltY.ja.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-L9-lBQbknp0.ar.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Notation for the Mean-3EF15AoRxyM.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-8HFOaRdDpek.en.vtt
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Part 12-Module 02-Lesson 05_Trees/16. Heapify-CAbDbiCfERY.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction to Data Wrangling-4cFsT9KBRs8.en.vtt
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Part 05-Module 01-Lesson 05_Data Quality/13. Auditing Accuracy-mADDYP7ldl4.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-buxApBhZCO0.ar.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/03. Types of Effect-Size Measures-FWSS2VadyBg.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-BHFxJmzw1gY.pt-BR.vtt
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Part 05-Module 01-Lesson 05_Data Quality/16. Auditing Consistency-bCAkWxApvQM.pt-BR.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-CvB2qkSk1Zc.pt-BR.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/07. Aggregation Operators 2-UZMklqP5-p4.zh-CN.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/21. Duration vs. Exposure Example-993P7ivCrnQ.pt-BR.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/10. AVG-diqCDztOL64.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-UMWsyRYnfPk.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/27. Communication-P36LwI-R2Vw.en.vtt
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/08. Hierarchies with Trina-ys8Cn0o5gNI.pt-BR.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/01. Instructor Introduction Juno Lee-to8Pp3PCOZo.en.vtt
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/02. What's Ahead-ggbCydfI1JM.zh-CN.vtt
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/03. Hierarchies with Trina-ys8Cn0o5gNI.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-a6oG3g7aKR4.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.en.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-a6oG3g7aKR4.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.zh-CN.vtt
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Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-NXbR9GQbtnk.pt-BR.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/04. COUNT-b4FCWAEGmLg.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-Hb2q-o4ElV4.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-2DwKMiFjGPE.pt-BR.vtt
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/16. Comparing Row to Previous Row-Z_x5ZJyDZog.en.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/10. Traditional Confidence Interval Methods-DmZwYHuz2eM.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/29. Let's Make a Bar Chart-PlhGAjAZFhw.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.ar.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/23. Connecting Errors and P-Values-hFNjd5l9CLs.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files from the Internet-UceKUJ07Bn8.pt-BR.vtt
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Part 21-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.zh-CN.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.zh-CN.vtt
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Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-qHk-FRWnYAo.pt-BR.vtt
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/02. Data Overview-u_qB4w4kL1o.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.zh-CN.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/06. Example of Sampling Distributions - Part I-1XezzP6kxUE.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/22. Decomposing Visualizations-iJ8t2FsPW4c.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/45. The Grammar of Graphics-AdRbdZhLn04.pt-BR.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/03. Your First JOIN-HkX9fkNRbU8.pt-BR.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/04. Describe Your Work Experiences-B1LED4txinI.es-MX.vtt
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/04. Describe Your Work Experiences-B1LED4txinI.es-MX.vtt
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences-B1LED4txinI.es-MX.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-mPN46IqnT1c.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.th.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion-SRXNBlvW-xw.ar.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-X_AS8NBngsk.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/21. Rankings of Visual Encodings-ycsXqX7T80Y.zh-CN.vtt
1.8 kB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/08. Rankings of Visual Encodings - Data Visualization and D3.js-ycsXqX7T80Y.zh-CN.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Common Table Expressions-qtEKO7B8bXQ.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -Vf-EK6vg6Uc.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.pt-BR.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-pn3MunHovMc.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-GTLvqNrAETc.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/29. Let's Make a Bar Chart-PlhGAjAZFhw.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots-llvIDIu3Sw8.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-3pT4mwTqxoA.pt-BR.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/06. 5 Number Summary to Variance-Ljhau0hrZ1g.pt-BR.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/07. Types Of Errors - Part I-aw6GMxIvENc.zh-CN.vtt
1.8 kB
Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-M_8000Yz_DA.pt-BR.vtt
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Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-qHk-FRWnYAo.en.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/07. How Databases Store Data-H0C9z_sRvLE.ar.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/22. How Databases Store Data-H0C9z_sRvLE.ar.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/10. Calculate SDs-bjk5m0wrj3w.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/18. Critical Values of Z-_vKCQnll45c.pt-BR.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/13. Mu-GXY-iMfZTn0.en.vtt
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Part 05-Module 01-Lesson 05_Data Quality/04. Sources of Dirty Data-h12MQ3d1Z1Y.pt-BR.vtt
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Part 12-Module 02-Lesson 05_Trees/16. Heapify-CAbDbiCfERY.pt-BR.vtt
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Part 19-Module 01-Lesson 02_Design/18. Tell A Story-_IdOUEhjVGI.zh-CN.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/04. Introduction to Hashing-8yik3RlDFgM.zh-CN.vtt
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Part 11-Module 01-Lesson 16_Tying It All Together/01. Introduction-8tm1144C4T0.zh-CN.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/18. ORDER BY Statement-wqj2As31LqI.zh-CN.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/01. Introduction -rkRn1Nh-6lg.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-XUZIGbX3JIg.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-SxCK2_82FfQ.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.es-ES.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/05. Assignment Operators-p_qfzL-x3Cs.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/41. The World Cup Narrative-nnqZR2GdcAA.ar.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/30. Arithmetic Operators-fgcJdiNECxI.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-Uf_KdjVT2Xg.ar.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-Uf_KdjVT2Xg.ar.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/46. OR Statement-DRmkKVhe6-s.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI-L_JV4fbRAfA.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/30. Rent - Increase n-UUn6ETq08SU.pt-BR.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/17. JSON Files In Python-8JdUknZP59Q.pt-BR.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.zh-CN.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/01. Introduction-Vnj2VNQROtI.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-2DwKMiFjGPE.ja.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/35. Summary of the Update Function-IVmBlMgErzY.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.zh-CN.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2-cpDTPUNDo4U.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.pt-BR.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-lWjaCJazJE0.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-TluBvgsphHQ.ar.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/11. In-Place vs. Not In-Place-STqN_v6Iz5o.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-UMWsyRYnfPk.pt-BR.vtt
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Part 12-Module 01-Lesson 02_Practice Behavioral Questions/04. Time When You Showed Initiative-29mkriaGT0E.zh-CN.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/05. Confidence Interval for a Difference In Means-8hrWGzjyhck.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place-STqN_v6Iz5o.ar.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/08. Darts-fSj1dwh7Kxc.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-3kH4ei9l4h8.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-sLEF-B1fkX8.es.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-_bnZEnWWqXQ.pt-BR.vtt
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Part 17-Module 01-Lesson 14_Regression/15. Fitting A Regression Line In Python-0CiMDbEUeS4.zh-CN.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/02. Why Do We Use Data Visualizations-iiOP4PE46f4.ar.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/31. Dependent Samples-kcTh3hJ1XCw.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/16. Subqueries-YWZ-bgnZWaM.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/49. Orienting and Drawing the Axes-I9-ysMlq-Xc.pt-BR.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/12. Which Distribution-tTb1k27rhgI.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.ja.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-MLGu66F25qU.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-MLGu66F25qU.es.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose-pBSQI8EmhvM.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.th.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/24. MM CLT-IAVgtiZLlOg.pt-BR.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-f7vNKm0Zci0.zh-CN.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/22. Having-D4gmN0vnk58.pt-BR.vtt
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Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-hxxa0KAkB1o.zh-CN.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/30. CASE Statements and Aggregations-asSXB6iD3z4.en.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/13. Dummy Variables Recap-r7Lek8rsIcg.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/32. From Dimple to D3-0yJzBWRQi5U.en.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Data Types-gT6EYlsLZkE.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/12. Generalize CI-7JS9PPQ6cN4.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.pt-BR.vtt
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Part 11-Module 01-Lesson 01_Welcome to Machine Learning/03. Introduction Pt. III-0ZuxGhiqo5U.ja.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.pt-BR.vtt
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Part 05-Module 01-Lesson 05_Data Quality/04. Sources of Dirty Data-h12MQ3d1Z1Y.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/28. Outlining the Update Function-k5ZZQ3ulwX4.pt-BR.vtt
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Part 21-Module 01-Lesson 03_Control Flow/07. Truth Value Testing-e52uw7ejV8k.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/39. Clarifying Sample SD-iRudjk53deY.zh-CN.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-_Z4d6-d-glM.en.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-_Z4d6-d-glM.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20-YaznAtppruA.zh-CN.vtt
1.8 kB
Part 11-Module 01-Lesson 02_Naive Bayes/38. Naive Bayes Mini-Project Video-UH2oSijkszo.ja.vtt
1.8 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-FpcCdcKFBKM.zh-CN.vtt
1.8 kB
Part 13-Module 01-Lesson 05_Dimple.js/05. A Simple HTTP Server-h8Fa24E_I5s.zh-CN.vtt
1.8 kB
Part 16-Module 03-Lesson 02_SQL Joins/01. Introduction to JOINs-YvZ010GU-Ck.pt-BR.vtt
1.8 kB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/20. When Does the CLT Not Work-uZGTVUEMfrU.pt-BR.vtt
1.8 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-Keh5GwaSWdk.ar.vtt
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/04. Gathering Data-r7BHGq_0P9Q.zh-CN.vtt
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Part 05-Module 01-Lesson 05_Data Quality/13. Auditing Accuracy-mADDYP7ldl4.en.vtt
1.8 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-DclTt9xqS4s.zh-CN.vtt
1.8 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/16. Performance Tuning 2-arMtEhSoq7E.zh-CN.vtt
1.8 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/26. Confidence Interval Case Breakdown-gycmvQqw-8s.zh-CN.vtt
1.8 kB
Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score-iHnjTqGPbVg.pt-BR.vtt
1.8 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-WCcnGQY771c.zh-CN.vtt
1.8 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-WCcnGQY771c.zh-CN.vtt
1.8 kB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/23. Pooled Variance Sum of Squares-H-1atcURVzk.zh-CN.vtt
1.8 kB
Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-CvTXyvw7QLc.zh-CN.vtt
1.8 kB
Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-1Hd1Bq1YxXg.zh-CN.vtt
1.8 kB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.ja.vtt
1.8 kB
Part 05-Module 02-Lesson 05_Deeper into SQL/12. What's a DB-API-06LsRU4pmkA.zh-CN.vtt
1.8 kB
Part 11-Module 01-Lesson 02_Naive Bayes/07. Intro To Stanley Terrain Classification-TwFhCeov85E.ar.vtt
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Part 17-Module 01-Lesson 13_Case Study AB tests/04. Business Example-Wzz7omSDfEk.zh-CN.vtt
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Part 19-Module 01-Lesson 02_Design/19. Same Data Different Stories-jSSnkz3QT5Y.zh-CN.vtt
1.8 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/16. Beginning to Build Our http Requests-ojd7xXOd_64.zh-CN.vtt
1.8 kB
Part 13-Module 01-Lesson 07_Narrative Structures/26. Thinking with Joins-HGQ25_ivLMQ.ar.vtt
1.8 kB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/02. Data Overview-u_qB4w4kL1o.en.vtt
1.8 kB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/16. Mean Number of Shoes-j3RQ-8l2nos.zh-CN.vtt
1.8 kB
Part 21-Module 01-Lesson 05_Scripting/02. Python Installation-2_P05aYChqQ.en.vtt
1.8 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/29. Formula for Location of Median-h3zyZHNyreM.zh-CN.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/24. MM CLT-IAVgtiZLlOg.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-3pT4mwTqxoA.ja.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-P6ZOr7JiMLk.en-US.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/09. Maps in D3-DAfs_MCYP0o.en.vtt
1.8 kB
Part 17-Module 01-Lesson 14_Regression/08. Correlation Coefficients-rL5Bn8Fi-zE.en.vtt
1.8 kB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/11. Correlation Coefficients-rL5Bn8Fi-zE.en.vtt
1.8 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/38. Something Fun-7kOZs5PLtqs.zh-CN.vtt
1.8 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/21. Sampling Observations-PsRMReOqccg.ja.vtt
1.8 kB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites-0ANDJ8i_deE.en.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/34. LIKE Operator-O5z6eWkNip4.zh-CN.vtt
1.8 kB
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.it.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-VkQwfVQ00EQ.pt-BR.vtt
1.8 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-P6ZOr7JiMLk.en.vtt
1.8 kB
Part 13-Module 01-Lesson 05_Dimple.js/13. Adding an Axis with Dimple-7okDT6V9Mmk.pt-BR.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/01. Introduction-AyeKXinJ3W8.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-8_SBvU8NYak.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-8_SBvU8NYak.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-TSw2AAaKxBA.es.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/19. DISTINCT-YDJEHkgKORY.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-wqvEtUA0n-s.en.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/33. Adding Bars and Text-EcwO8YPrn-M.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/03. Parts of Speech Analogy for Data Vis-bO8clma7Mnc.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/40. Creating Time and Attendance Scales-PgAp8ob4hIM.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/13. Tracking Down the Remaining Problems-Xblj5rT9i0M.zh-CN.vtt
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/04. Describe Your Work Experiences-B1LED4txinI.en.vtt
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/04. Describe Your Work Experiences-B1LED4txinI.en.vtt
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences-B1LED4txinI.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/15. Formula of Entropy-NHAatuG0T3Q.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/28. How Visualizations can Save Lives-VUllIatQ3tI.ar.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/02. Histograms-4t10RgUv2Fc.pt-BR.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/01. Confidence Intervals Introduction-crleT4000ak.pt-BR.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/12. Other Language Associated With Confidence Intervals-9KYVRx7-llg.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.zh-CN.vtt
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Part 09-Module 01-Lesson 02_R Basics/15. Data Munging-q_Ghc6VsDo0.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-iu6CxSkq-wg.en.vtt
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Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3--XfG5hXveiE.ar.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/24. Conclusions In Hypothesis Testing-I0Mo7hcxahY.zh-CN.vtt
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/14. COALESCE-86vgu-ECBCQ.pt-BR.vtt
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Part 11-Module 01-Lesson 14_Validation/15. Validation Mini-Project Video-dlbeMlRoFd4.en.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/03. Fitting A Multiple Linear Regression Model-EZNvBF66_b0.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/01. Intro-jOhaqX_9oy8.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-mIBKd-JBnXY.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-8oM8KjsntG8.en-US.vtt
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Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel-j5tA__Dq-sQ.zh-CN.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/15. Two Useful Theorems-jQ5i7CALdRQ.ar.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/01. Introduction -rkRn1Nh-6lg.zh-CN.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-q46nO0mznXM.pt-BR.vtt
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Part 12-Module 02-Lesson 05_Trees/02. Tree Basics-oaxLPzaXRDc.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/30. Thinking with Venn Diagrams-C1aHeMSeIdk.zh-CN.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-UXLEe6bNpM4.ar.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-bcwFahJsww0.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-8oM8KjsntG8.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/32. What Happened-NSuT87J4V-g.zh-CN.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-_Z4d6-d-glM.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/04. Picking the Most Suitable Metric-GAfPvj2SSiE.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/16. -_mge9UU-gpQ.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-hUmXWHOPxpI.pt-BR.vtt
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Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules Part II-aASigWQ_XU0.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-_Z4d6-d-glM.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.en.vtt
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/05. Source Files On Hand-PjP-EaeXTiY.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/12. Plot Colors for Qualitative Factors-2ZVGl6LrOPw.ja.vtt
1.8 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-3kH4ei9l4h8.ja.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-plnMY4iATyU.zh-CN.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/22. Variability Example-kTXI_wnTbVk.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-2ieszOqnpWs.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-e6pJfNbQEKk.pt-BR.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/05. CREATE TABLE and Types-7DCw86WMpYo.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/60. Context for the Reader-_GkNEO9qeWI.pt-BR.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.es-ES.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-P8ZxaAQTZXQ.zh-CN.vtt
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Part 09-Module 01-Lesson 01_What is EDA/09. Course Overview-W8N0aSMPff8.ja.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/18. Multicollinearity VIFs-uiF3UcDWwPI.zh-CN.vtt
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Part 21-Module 01-Lesson 04_Functions/01. Introduction-p5L4rTV1Pgk.ar.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-a6oG3g7aKR4.pt-BR.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/27. Conclusion-IanoSiET2nA.ar.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-a6oG3g7aKR4.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.pt-PT.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.pt-PT.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.ja.vtt
1.8 kB
Part 17-Module 01-Lesson 06_Conditional Probability/01. Introduction to Conditional Probability-Ok8948Wcbmo.en.vtt
1.8 kB
Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-BRL0ZuvBm0U.ko.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/27. Results from Sample-ypIyvJyZAs8.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/02. Normalized Design Part One-LQq5F77ANiY.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/04. Iterative Process-m2qDeWrGIDI.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/18. Averaging Locations-GLQJukg-0fQ.zh-CN.vtt
1.8 kB
Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.ja.vtt
1.8 kB
Part 11-Module 01-Lesson 02_Naive Bayes/04. Features and Labels Musical Example-rnv0-lG9yKU.en.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.ar.vtt
1.8 kB
Part 12-Module 02-Lesson 06_Graphs/04. Connectivity-4x6u2KtNDg4.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/14. Anscombe’s Quartet-Ftp3mmItV-k.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/20. The Martini Glass-h8b8SOsSiT4.pt-BR.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Anscombe’s Quartet-Ftp3mmItV-k.zh-CN.vtt
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Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Using With-OQ-Y0mMjm00.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-TU63rBOwXQ8.ar.vtt
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Part 11-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites-0ANDJ8i_deE.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.pt-BR.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction to Data Wrangling-4cFsT9KBRs8.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-3uUwfgOUT0Y.ar.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/05. CREATE TABLE and Types-7DCw86WMpYo.en.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/01. Introduction-aAmMK8tGEYc.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age-GFKRNBnFGVU.ar.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-P6ZOr7JiMLk.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-MV_e0z9kFjM.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/25. Sorting the Data for Drawing Order-X-zVfcuacD4.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.es-ES.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/11. Data Vis in Data Science-e_-61K3jK1Y.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/21. Adding SVG Elements-Vx9n2qXwL6w.en-US.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example-Ae_UOATWmDM.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 1-V7STsHoZ2gA.en.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/09. Handling Attributes-YSEGZMBbxTk.pt-BR.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-KhGfaSWoEn0.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-KrZpJwPlSbA.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-IMWsjjIeOrY.zh-CN.vtt
1.8 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/21. Adding SVG Elements-Vx9n2qXwL6w.en.vtt
1.8 kB
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.en.vtt
1.8 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/21. Shape of Distribution When n Increases-kJ4Y8a1rOkY.pt-BR.vtt
1.8 kB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/22. Find P-Value-TVN4JfSm144.pt-BR.vtt
1.8 kB
Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-djTM5fADIVs.zh-CN.vtt
1.8 kB
Part 13-Module 01-Lesson 05_Dimple.js/11. Chart Layout and Group Tags--2yj49s7v5w.zh-CN.vtt
1.8 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-tfhsgVCX2Ao.zh-CN.vtt
1.8 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/11. In-Place vs. Not In-Place-TVyv8acRPrs.ar.vtt
1.8 kB
Part 13-Module 01-Lesson 05_Dimple.js/27. Bar Chart The Bad-FCapLzYUQSo.pt-BR.vtt
1.8 kB
Part 13-Module 01-Lesson 07_Narrative Structures/60. Context for the Reader-_GkNEO9qeWI.en-US.vtt
1.8 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/23. The Radius Scale-Rkrj1HjaMQM.pt-BR.vtt
1.8 kB
Part 16-Module 03-Lesson 03_SQL Aggregations/22. Having-D4gmN0vnk58.en.vtt
1.8 kB
Part 17-Module 01-Lesson 14_Regression/02. Introduction to Machine Learning-pLcFPPI1L-0.zh-CN.vtt
1.8 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place-TVyv8acRPrs.ar.vtt
1.8 kB
Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.en.vtt
1.8 kB
Part 13-Module 01-Lesson 04_Design Principles/45. The Grammar of Graphics-AdRbdZhLn04.en.vtt
1.8 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/09. Maps in D3-DAfs_MCYP0o.pt-BR.vtt
1.8 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-nsG26Dz9z44.en.vtt
1.8 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Data in the Real World-HmipezTjTDY.pt-BR.vtt
1.8 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.en.vtt
1.8 kB
Part 17-Module 01-Lesson 16_Logistic Regression/06. Interpreting Results-UPOxxbKu6CQ.zh-CN.vtt
1.8 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.en.vtt
1.8 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-3kH4ei9l4h8.en.vtt
1.8 kB
Part 11-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm-hGKY6BAqJ6o.zh-CN.vtt
1.8 kB
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-UjyPKvNHz4A.pt-BR.vtt
1.8 kB
Part 16-Module 03-Lesson 01_Basic SQL/09. Types Of Statements-vLvJbIz94C4.pt-BR.vtt
1.8 kB
Part 18-Module 02-Lesson 01_Gathering Data/22. Types Of Statements-vLvJbIz94C4.pt-BR.vtt
1.8 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/19. What is Notation-MaHV5cKfcmE.pt-BR.vtt
1.8 kB
Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-eeV5K5HKVx4.pt-BR.vtt
1.8 kB
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-NXbR9GQbtnk.en.vtt
1.8 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ZhWxuf5czTA.ar.vtt
1.8 kB
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.en.vtt
1.8 kB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Notation Parameters vs. Statistics-webref_dLrA.pt-BR.vtt
1.8 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-93y6ms_fuQQ.pt-BR.vtt
1.8 kB
Part 13-Module 01-Lesson 05_Dimple.js/07. Javascript Debugger-AzbaV5CT9es.ar.vtt
1.8 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/10. NumPy Index Arrays-93y6ms_fuQQ.pt-BR.vtt
1.8 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-8_SBvU8NYak.en.vtt
1.8 kB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-8_SBvU8NYak.en.vtt
1.8 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-iu6CxSkq-wg.pt-BR.vtt
1.8 kB
Part 14-Module 01-Lesson 05_Analyzing Results/03. Choosing Invariants-qCnbDgy2yHk.zh-CN.vtt
1.8 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-kFKsCAyiPuY.pt-BR.vtt
1.7 kB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-kFKsCAyiPuY.pt-BR.vtt
1.7 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-3pT4mwTqxoA.en.vtt
1.7 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.en.vtt
1.7 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/01. Welcome!-KJT4Z0xpHns.zh-CN.vtt
1.7 kB
Part 13-Module 01-Lesson 07_Narrative Structures/32. From Dimple to D3-0yJzBWRQi5U.pt-BR.vtt
1.7 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/30. Filtering-vXGDYzAo22Y.en.vtt
1.7 kB
Part 05-Module 01-Lesson 05_Data Quality/16. Auditing Consistency-bCAkWxApvQM.en.vtt
1.7 kB
Part 09-Module 01-Lesson 01_What is EDA/09. Course Overview-W8N0aSMPff8.pt-BR.vtt
1.7 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-iu6CxSkq-wg.ja.vtt
1.7 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.ja.vtt
1.7 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/24. Adjusting the Map Aesthetics-tc1Aai8e-w0.pt-BR.vtt
1.7 kB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/04. Describe Your Work Experiences-B1LED4txinI.zh-CN.vtt
1.7 kB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/04. Describe Your Work Experiences-B1LED4txinI.zh-CN.vtt
1.7 kB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences-B1LED4txinI.zh-CN.vtt
1.7 kB
Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Tp5WCAJiCRY.ar.vtt
1.7 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/30. Filtering-vXGDYzAo22Y.pt-BR.vtt
1.7 kB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/06. DF - Marginal Totals-PBcd_dxiFbE.zh-CN.vtt
1.7 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/02. One Number to Describe Data-6QfvhQ0En0E.ar.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/08. Continuous vs. Discrete Data-BzgZebZD9kk.pt-BR.vtt
1.7 kB
Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.zh-CN.vtt
1.7 kB
Part 21-Module 01-Lesson 01_Why Python Programming/03. L1 03 Programming In Python V4-O1cTNYAjeeg.ar.vtt
1.7 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/09. What We Need to Compare the Means-y27MBpbnP48.pt-BR.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-_bnZEnWWqXQ.en.vtt
1.7 kB
Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-97v0kEWjcmg.ar.vtt
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Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.ar.vtt
1.7 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/21. Duration vs. Exposure Example-993P7ivCrnQ.en.vtt
1.7 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/29. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA.en.vtt
1.7 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/26. Use Measures of Center to Compare-KFK1L4hUW80.pt-BR.vtt
1.7 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/11. Two-Tailed Test-VFS9mGdkU-M.pt-BR.vtt
1.7 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/01. Introduction-aAmMK8tGEYc.en.vtt
1.7 kB
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.ja.vtt
1.7 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.en.vtt
1.7 kB
Part 11-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.pt-BR.vtt
1.7 kB
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-t2Nq3MFK_pg.zh-CN.vtt
1.7 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-q46nO0mznXM.en.vtt
1.7 kB
Part 13-Module 01-Lesson 05_Dimple.js/13. Adding an Axis with Dimple-7okDT6V9Mmk.en.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/05. Source Files On Hand-PjP-EaeXTiY.en.vtt
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Part 19-Module 01-Lesson 02_Design/14. Designing for Color Blindness-k4iTzS7t2U4.pt-BR.vtt
1.7 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/01. Introduction-QXxtu_gdWQs.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-wqvEtUA0n-s.ja.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-t0iflCpBUDA.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/19. Probability Conclusion-dsVKoXymYDU.pt-BR.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/02. Introduction-QXxtu_gdWQs.pt-BR.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-_Lp_3KUltFk.en.vtt
1.7 kB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/02. Data Overview-u_qB4w4kL1o.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-k8Ru6RQJbd4.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/09. Handling Attributes-YSEGZMBbxTk.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/49. Orienting and Drawing the Axes-I9-ysMlq-Xc.en.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-k8Ru6RQJbd4.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/01. Intro-8y2JZ2gEl1k.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-2ieszOqnpWs.ja.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/13. Motivation for Other JOINs-3qdv1Ojc9Og.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/30. R Squared Metric for Regression-yDJEP-XSWdU.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/40. Notation for Difference-r1X81SXRLKI.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts-i6nppkOcNoE.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.ar.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 2-9YPOlROXNZM.ar.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2-elZCLxVvJrY.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/09. Be Skeptical Outliers and Anomalies-kAisC2wRGBU.pt-BR.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/16. GROUP BY Part II-0HQ-TshNNQA.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.th.vtt
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Part 12-Module 02-Lesson 02_List-Based Collections/01. Welcome to Collections-cZORvZq-tI0.en-US.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/14. -z-mXs7Rl-Ys.zh-CN.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-_Lp_3KUltFk.pt-BR.vtt
1.7 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-8HFOaRdDpek.zh-CN.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/22. in Operator-8iX-7hwKX1Q.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-t0iflCpBUDA.en.vtt
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Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-wl3gjMMrYwM.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-8HFOaRdDpek.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-CvB2qkSk1Zc.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/21. Sampling Observations-PsRMReOqccg.en.vtt
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Part 12-Module 02-Lesson 02_List-Based Collections/01. Welcome to Collections-cZORvZq-tI0.en.vtt
1.7 kB
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-UjyPKvNHz4A.en.vtt
1.7 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/28. Probability of Obtaining Mean-ErwocwQVgYE.zh-CN.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/14. The Central Limit Theorem-ag3TB5UGu_g.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/01. Introduction-0ydaJl3wCkU.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/08. The Experiment Page--GlHaeB-vic.ar.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.es-ES.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.es-ES.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.zh-CN.vtt
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Part 11-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video-GJviz-sIq9w.ar.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment -YrX-oiFilyA.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-9piyE5in7YE.zh-CN.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/15. Roll 1 Die-oJXYNArEk8k.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-ZO7y9tsSQ0A.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.ja.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.ja.vtt
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Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-8ZvLpWDITn4.en.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/08. Extracting Data-OeiBJ_D-ZsM.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-TBJY7UsKtYU.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.hr.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/12. Caution with Class Selections-fP30uBJljNk.en-US.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2 Solution-ncqhpqt0Mik.ar.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction to Data Wrangling-4cFsT9KBRs8.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-1R44jvxIPJY.ar.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.ar.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/12. Caution with Class Selections-fP30uBJljNk.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-8IzQG_2WAcs.ar.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/01. Introduction to Data Visualization-MUZXLvBI2sw.en.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/01. Introduction to Data Visualization-MUZXLvBI2sw.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-mZgPfxFOFRE.pt-BR.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/24. There Must Be A Better Way-oBp8YX2AgJw.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance-QReeBef_7vM.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores-2OKqKX7DnMQ.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/02. Alpha Levels-pjBOYFAkNME.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/11. Data Vis in Data Science-e_-61K3jK1Y.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.en.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess-XoQr2hohdvI.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-CvB2qkSk1Zc.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/38. Naive Bayes Mini-Project Video-UH2oSijkszo.en.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/13. Motivation for Other JOINs-3qdv1Ojc9Og.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-VUfaXWrr3oY.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/32. Visualizing Regression-zQAHZhcsXoQ.zh-CN.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/08. Dummy Variables--QTgDd-fZuA.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/21. Storing Data-hcosH34b-yw.pt-BR.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5-tEmdl6zhvgA.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/29. Correcting Color-7vaHp4caWxw.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/28. Outlining the Update Function-k5ZZQ3ulwX4.en.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/10. Integrity and Mindset-zCOr3O50gQM.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-VkQwfVQ00EQ.en.vtt
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Part 17-Module 01-Lesson 14_Regression/17. How Do We Know If Our Model Fits Well-0vPtPAqMHJE.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score-1V7JzqCfe9o.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/44. Parsing Overview and Parsing Attendance-_tVC3JuW7to.en.vtt
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Part 19-Module 01-Lesson 02_Design/14. Designing for Color Blindness-k4iTzS7t2U4.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.es.vtt
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Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-8ZvLpWDITn4.pt-BR.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/01. Confidence Intervals Introduction-crleT4000ak.en.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/13. Dummy Variables Recap-r7Lek8rsIcg.en.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/10. Assessing Vs Exploring V2 -hVFZ6jFKOso.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/09. Be Skeptical Outliers and Anomalies-kAisC2wRGBU.ja.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files from the Internet-UceKUJ07Bn8.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/23. Measures of Center-eNoE9hSDxPA.pt-BR.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/13. Karma-cNFMJpVQlKY.pt-BR.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/01. Introduction to JOINs-YvZ010GU-Ck.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/38. Naive Bayes Mini-Project Video-UH2oSijkszo.pt-BR.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/22. in Operator-8iX-7hwKX1Q.en.vtt
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Part 11-Module 01-Lesson 03_SVM/13. Nonlinear SVMs-6UgInp_gf1w.ja.vtt
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Part 11-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/18. Critical Values of Z-_vKCQnll45c.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-GTLvqNrAETc.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.en-US.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-QJxhBCWK6BQ.zh-CN.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/01. Introduction to Logistic Regression-P_f2RjjnPEg.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/19. Pooled Standard Error-iub8yWiO84I.zh-CN.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/10. Traditional Confidence Interval Methods-DmZwYHuz2eM.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-gBdKhmtrtG8.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-zxnijlBCSpE.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-CuMPjPESfY0.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/04. Features and Labels Musical Example-rnv0-lG9yKU.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.en.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/02. Technical Interlude-QWA06Ro4ix0.ar.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/22. Bootstrapping-42j3YclcZ4Q.zh-CN.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment -YrX-oiFilyA.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/26. Sum of Squares-fktfjG1SnkI.pt-BR.vtt
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Part 12-Module 01-Lesson 01_Ace Your Interview/01. Introduction-pg4HUMgKLxI.en.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/17. JSON Files In Python-8JdUknZP59Q.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-sLEF-B1fkX8.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-VkQwfVQ00EQ.ja.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/21. Information Gain-KYieR9y-ue4.ar.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/11. Z-Table-hSAxcGBxbds.zh-CN.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations--InZYjwPsKs.ar.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.zh-CN.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-oZkDSuhBEkE.zh-CN.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/22. NEW D3 Scale Syntax-ba-Luz-Ip0Y.zh-CN.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/28. Variability Summary-sDejdrYe8cg.ar.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions-EvhIgrXtOao.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations--InZYjwPsKs.ar.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value-6Z3BJWRuOAE.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots--gIxCjLXCEs.ar.vtt
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Part 11-Module 01-Lesson 14_Validation/15. Validation Mini-Project Video-dlbeMlRoFd4.pt-BR.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/02. Parch Posey Database-JOMI560DgXg.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/01. Finding Stories-vVWFVaiWomw.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/23. The Radius Scale-Rkrj1HjaMQM.en-US.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/24. Adjusting the Map Aesthetics-tc1Aai8e-w0.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings-0-LYyC_70jk.ar.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/07. The One Thing SQL is Terrible At-wrjCB1abNyM.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/10. IQR-d7J0y_PSP2I.pt-BR.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/07. Confidence Intervals Applications-C0wgmeRx9yE.pt-BR.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/15. Who Has More Shoes-ODDruv2Qkdg.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/23. The Radius Scale-Rkrj1HjaMQM.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/04. Picking the Most Suitable Metric-GAfPvj2SSiE.en.vtt
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/16. Comparing Row to Previous Row-Z_x5ZJyDZog.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.th.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/12. One-Sample t-Test-QyjjSIvJ_F4.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.it.vtt
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Part 13-Module 01-Lesson 04_Design Principles/04. Chart Types-0a5oJR6TwAs.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/24. Are your Results Just Noise-LjuF5M6ymPA.zh-CN.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/09. Handling Attributes-YSEGZMBbxTk.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-eeV5K5HKVx4.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 1-V7STsHoZ2gA.zh-CN.vtt
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Part 09-Module 01-Lesson 01_What is EDA/04. Aude's Interest in Data-DDNSMG_RltY.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.pt-BR.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-tGHQsk1SGGU.zh-CN.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 1-APRpwqFpGwI.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-AO8vSyAtfV4.ar.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-aznzJPXavDg.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/24. Redundant Encodings-RU3rI_pO8Rc.pt-BR.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/06. Checking Invariants, Part 2-Mftti4FSjn4.ar.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/22. Outliers Advice-BhhDoTgYQmI.pt-BR.vtt
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Part 21-Module 01-Lesson 05_Scripting/02. Python Installation-2_P05aYChqQ.zh-CN.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/20. When Does the CLT Not Work-uZGTVUEMfrU.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/23. CI Bounds-T9VX2KvzJ-k.en.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-vfEi3aOawTI.ar.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/01. Choose Your own Algorithm-tpbHNLv-HT0.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/23. Measures of Center-eNoE9hSDxPA.en.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/11. Z-1MZnEo0UVX4.pt-BR.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/21. Querying Arrays Using Scalars-8uhfnWgiBHM.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-2DwKMiFjGPE.zh-CN.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.en.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/04. Further Motivation-sjGxUKrbKoI.pt-BR.vtt
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Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/17. Plotting in Pandas-ujJShz9YfAU.ar.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/27. Bar Chart The Bad-FCapLzYUQSo.en.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/18. Plotting in Pandas-ujJShz9YfAU.ar.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.ar.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download II-T4iFJoHb_qU.ar.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/28. Show Me-Jpk99mgmwaA.ar.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/01. Introduction-QXxtu_gdWQs.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-S1yjJWWza7g.zh-CN.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate-eu1gO_76pSY.pt-BR.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/02. Introduction-QXxtu_gdWQs.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/15. Bigger Sample, Smaller CI-DRarpjC23kc.en.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-_bnZEnWWqXQ.zh-CN.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.ar.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations-q5PjL9GkVtM.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-KuihzV_LLAE.pt-BR.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations-q5PjL9GkVtM.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/21. Linear Regression Errors-A4nPMEOcUd4.ar.vtt
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Part 09-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-GTLvqNrAETc.ja.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/02. A New Enron Feature-m2-LkgEfLO0.zh-CN.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/21. Adding SVG Elements-Vx9n2qXwL6w.zh-CN.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 1-V7STsHoZ2gA.pt-BR.vtt
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Part 05-Module 01-Lesson 05_Data Quality/04. Sources of Dirty Data-h12MQ3d1Z1Y.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/44. Parsing Overview and Parsing Attendance-_tVC3JuW7to.pt-BR.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 2-CyeB16-eGSg.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/02. What to Do First-TgAIx_NFaD8.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/40. Creating Time and Attendance Scales-PgAp8ob4hIM.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.ar.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-M_8000Yz_DA.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-93y6ms_fuQQ.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/24. The Facebook Offering Animation-s7h2tH6z9Rg.pt-BR.vtt
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/02. Data Overview-V-iPdJfrscQ.ar.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/10. NumPy Index Arrays-93y6ms_fuQQ.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-ljBJOXJTR9A.pt-BR.vtt
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Part 09-Module 01-Lesson 01_What is EDA/07. Our Approach for This Course-dBsf-szQ00s.pt-BR.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score-iHnjTqGPbVg.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-7lKhG9bIMhs.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-KuihzV_LLAE.en.vtt
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Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.ja.vtt
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Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-2ieszOqnpWs.en.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Ilu1JjjAbwA.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/24. The Facebook Offering Animation-s7h2tH6z9Rg.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-4hoT_su75AQ.pt-BR.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-QCakJ5gxF5w.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.ja.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/04. COUNT-b4FCWAEGmLg.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-a6oG3g7aKR4.zh-CN.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/01. Introduction-Vnj2VNQROtI.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.ar.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-a6oG3g7aKR4.zh-CN.vtt
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Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-3r8OR2yQ-KI.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/05. Visualizations in Data Science-UCKGGQ4LFjo.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data-D7m25cvqUpw.ja.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/28. Conclusion-rrSNkPGJmTc.pt-BR.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/06. Ethical Considerations for Diversion-Zf0XzYNsado.zh-CN.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-KhGfaSWoEn0.en.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/08. Source Scraping Webpages-ZqTad6Usf9g.pt-BR.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.ja.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.zh-CN.vtt
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Part 12-Module 02-Lesson 02_List-Based Collections/02. Lists-KUQSgUMtyv0.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-KrZpJwPlSbA.es.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/12. Affect t-Statistic-c6vE21UVksU.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2-cpDTPUNDo4U.en.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/22. Outro -lfWT0kLfe8c.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/44. Adding Events to Buttons-UXRemP4hIyw.ar.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/14. Multiple Metrics Example 2-m0E26ndQBNo.zh-CN.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Why the Standard Deviation-XlTBvjQ2t8w.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/34. Spreadsheet SD-sXeVydVAv7Q.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/19. Engagement Ratio-EdIcXVIYX88.zh-CN.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/21. Size vs. Power Trade-Off-bnTIVGBkKhM.pt-BR.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.ar.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/26. Use Measures of Center to Compare-KFK1L4hUW80.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/08. Aggregations-TE9uvPwvpu4.ar.vtt
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Part 09-Module 01-Lesson 01_What is EDA/09. Course Overview-W8N0aSMPff8.en.vtt
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Part 11-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.pt-BR.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6-eqFgLu0eqBE.pt-BR.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/02. Histograms-4t10RgUv2Fc.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/13. Mu-GXY-iMfZTn0.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/06. Dimple Bar Chart Code Overview-vuxN6EC_gso.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-k8Ru6RQJbd4.en.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/06. Subqueries Part II-jko-RrZd0R8.en.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-k8Ru6RQJbd4.en.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/08. Infinitely Small-9ftDJRsfEUI.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250-mPcWDYTRDs8.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-tjEua8efugg.hi.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/24. There Must Be A Better Way-oBp8YX2AgJw.pt-BR.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/05. CREATE TABLE and Types-7DCw86WMpYo.zh-CN.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/08. Features != Information-GOrv8faKHV4.en.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/01. Instructor Introduction Juno Lee-to8Pp3PCOZo.zh-CN.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-PXNaLWJ5SKg.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-Z5nOpgKYYj4.ar.vtt
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Part 21-Module 01-Lesson 03_Control Flow/07. Truth Value Testing-e52uw7ejV8k.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.ja.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.ar.vtt
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Part 19-Module 01-Lesson 02_Design/02. Lesson Overview-Gg77PqkQkhs.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/26. Use Measures of Center to Compare-KFK1L4hUW80.es.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-KrZpJwPlSbA.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/18. Hypotheses-FDcgsIOTv94.pt-BR.vtt
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Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation-Mak839YmmrA.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-QII0tSAIex0.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/58. Juxtaposition and Comparison-abaD-wvlbkg.pt-BR.vtt
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Part 21-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/32. What Happened-vD9iXeq3PKc.zh-CN.vtt
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Part 15-Module 01-Lesson 02_Design Principles/01. Introduction-Q0lZkNF6O0g.pt-BR.vtt
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Part 19-Module 01-Lesson 02_Design/01. Introduction-Q0lZkNF6O0g.pt-BR.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/10. Less than 240-xUkquw-73BY.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/15. Who Has More Shoes-ODDruv2Qkdg.en.vtt
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components-DVvLiKedRw4.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-8oM8KjsntG8.ja.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/28. Conclusion-rrSNkPGJmTc.en.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 -Ngl_TsqhMsc.ar.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-4Aj_qdImmGo.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/26. Use Measures of Center to Compare-KFK1L4hUW80.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.en.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Subqueries Using WITH-IszTmDKyKHI.pt-BR.vtt
1.6 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Why the Standard Deviation-XlTBvjQ2t8w.en.vtt
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Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.th.vtt
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Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Using With-OQ-Y0mMjm00.zh-CN.vtt
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Part 12-Module 02-Lesson 05_Trees/16. Heapify-CAbDbiCfERY.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.zh-CN.vtt
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Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-5j6VZr8sHo8.ar.vtt
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Part 12-Module 02-Lesson 06_Graphs/04. Connectivity-4x6u2KtNDg4.zh-CN.vtt
1.6 kB
Part 16-Module 03-Lesson 01_Basic SQL/15. LIMIT Statement-cCPHNNhBgpQ.zh-CN.vtt
1.6 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/12. Variance Standard Deviation Final Points-vXUgp2375j4.zh-CN.vtt
1.6 kB
Part 18-Module 02-Lesson 01_Gathering Data/08. Source Scraping Webpages-ZqTad6Usf9g.en.vtt
1.6 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-kFKsCAyiPuY.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-kFKsCAyiPuY.es.vtt
1.6 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/27. Klout Parameters-wV-6gQepmn0.en.vtt
1.6 kB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components-DVvLiKedRw4.en.vtt
1.6 kB
Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.ar.vtt
1.6 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-wqvEtUA0n-s.zh-CN.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/30. CASE Statements and Aggregations-asSXB6iD3z4.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/24. Redundant Encodings-RU3rI_pO8Rc.en.vtt
1.6 kB
Part 17-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.ja.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-VBs6D4ggnYY.ja.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-eZ_yCrh4740.pt-BR.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-kutWDS1chik.ar.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-ljBJOXJTR9A.es.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/10. Less than 240-xUkquw-73BY.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/29. Decision Errors-4QMqg8izUac.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/21. Conclusion-JUI9VHvwI08.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.ja.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/05. COUNT NULLs-ngxgqfFFFLQ.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/21. Conclusion-JUI9VHvwI08.ar.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/07. Intro To Stanley Terrain Classification-TwFhCeov85E.ja.vtt
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Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-7LGaeYfvRug.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.ar.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/05. Assignment Operators-p_qfzL-x3Cs.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.zh-CN.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/03. Unit of Diversion Example-_-BxFJTBNMM.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data-vhl-SADfti8.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/10. Dimple Axes, Series and Fields-nSqsoDChbEU.ar.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/01. Introduction to Data Visualization-MUZXLvBI2sw.zh-CN.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Notation Parameters vs. Statistics-webref_dLrA.en.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/01. Introduction to Data Visualization-MUZXLvBI2sw.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-MLGu66F25qU.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-MLGu66F25qU.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/08. Extracting Data-OeiBJ_D-ZsM.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-_c_chcNiHyo.ar.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/35. Visualization and D3 Basics-ueKb1OghNEU.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/05. Approximate Margin of Error-P4gLGxQrKjY.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.ar.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/29. Let's Make a Bar Chart-PlhGAjAZFhw.zh-CN.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/14. Correct Interpretations of Confidence Intervals-IhYv_SlN7e8.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/18. Hypotheses-FDcgsIOTv94.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-xPZOSx1q_dg.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-xPZOSx1q_dg.pt-BR.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/35. L2 01 Compound Data Structures V1-jmQ8IKvQgBU.pt-BR.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/03. Projects and Progress-Z9ZLMQWsbsk.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample-9na_mOWP7pw.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/18. Better Sample-9na_mOWP7pw.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-n0lluEhKUfQ.ja.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6-eqFgLu0eqBE.en.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Data in the Real World-HmipezTjTDY.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-JsFlZfNpVl4.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-n0lluEhKUfQ.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-gBdKhmtrtG8.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/20. The Martini Glass-h8b8SOsSiT4.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/25. Margin of Error-slBW5Neh2cs.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-kFKsCAyiPuY.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-kFKsCAyiPuY.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data-D7m25cvqUpw.pt-BR.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/08. Hash Maps-A-ahUVi8pYQ.en-US.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/58. Juxtaposition and Comparison-abaD-wvlbkg.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-zlopUR9utUY.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-zlopUR9utUY.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/22. Find P-Value-TVN4JfSm144.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/16. Indulge Curiosity-9HnRVGjqNqE.ar.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/01. Introduction-Vnj2VNQROtI.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/15. Data Munging-q_Ghc6VsDo0.ja.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video-sJzKx_FiMXA.zh-CN.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/08. Hash Maps-A-ahUVi8pYQ.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/32. From Dimple to D3-0yJzBWRQi5U.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.en.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/01. Choose Your own Algorithm-tpbHNLv-HT0.en.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/03. Fitting A Multiple Linear Regression Model-EZNvBF66_b0.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance-QReeBef_7vM.en.vtt
1.6 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/50. Goodbye and Keep Learning-B4EKdtRmv60.en.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/37. IN Operator-_JPO7wwX3uA.pt-BR.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/20. Conclusion -d_nKtLo5WYA.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.pt-BR.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-eeV5K5HKVx4.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.zh-CN.vtt
1.6 kB
Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-gg7SAMMl4kM.ar.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-MLGu66F25qU.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-MLGu66F25qU.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/12. Generalize CI-7JS9PPQ6cN4.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation-Mak839YmmrA.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/19. Adding the Series and Drawing the Chart-2zcZXJzW0aw.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-mIBKd-JBnXY.en.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection-S-xe0-XNo4I.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size-rS6udGwrN90.pt-BR.vtt
1.6 kB
Part 11-Module 01-Lesson 03_SVM/11. SVM Decision Boundary-8hEjeR0qLnA.ar.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/10. Assessing Vs Exploring V2 -hVFZ6jFKOso.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/12. Data-d7aERRVkccY.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/12. Data-d7aERRVkccY.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/29. Decision Errors-TJ_p0xBI9bI.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/50. Goodbye and Keep Learning-B4EKdtRmv60.pt-BR.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/05. Source Files On Hand-PjP-EaeXTiY.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files from the Internet-UceKUJ07Bn8.zh-CN.vtt
1.6 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/07. Significance-FGtU7YDLX2Y.pt-BR.vtt
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Part 12-Module 01-Lesson 05_Interview Practice/02. Describe your latest data project-wkWDrSBBtz0.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-UNqgFhKvCL4.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-mZgPfxFOFRE.en.vtt
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Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.pt-BR.vtt
1.6 kB
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-ZULplTNbIIs.ko.vtt
1.6 kB
Part 09-Module 01-Lesson 02_R Basics/15. Data Munging-q_Ghc6VsDo0.en.vtt
1.6 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-8oM8KjsntG8.zh-CN.vtt
1.6 kB
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-ZULplTNbIIs.pt-PT.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-Bb2K_pql26Y.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.ar.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Intro -FnUrE4dhgh8.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/11. Two-Tailed Test-VFS9mGdkU-M.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/09. Maps in D3-DAfs_MCYP0o.zh-CN.vtt
1.6 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (Before Cleaning)-jJH3H8Rqv8s.ar.vtt
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Part 09-Module 01-Lesson 02_R Basics/16. Advice for Data Scientists-FdkhUOtHIFg.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/09. Be Skeptical Outliers and Anomalies-kAisC2wRGBU.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-3pT4mwTqxoA.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/49. Orienting and Drawing the Axes-I9-ysMlq-Xc.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ZhWxuf5czTA.pt-BR.vtt
1.6 kB
Part 13-Module 01-Lesson 04_Design Principles/08. Unemployment Line Plot-EbD9ufptNd0.pt-BR.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/14. Correct Interpretations of Confidence Intervals-IhYv_SlN7e8.pt-BR.vtt
1.6 kB
Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-095MTpItufM.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-hUmXWHOPxpI.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.es.vtt
1.6 kB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.es.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-RfYFqGPxMQM.ar.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-ljBJOXJTR9A.en.vtt
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Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-iCTPBcowJRY.en.vtt
1.6 kB
Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-FLpXmoHp7eE.ar.vtt
1.6 kB
Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-FLpXmoHp7eE.ar.vtt
1.6 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-Vp43h6ZRyoQ.ar.vtt
1.6 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/21. Querying Arrays Using Scalars-8uhfnWgiBHM.en.vtt
1.6 kB
Part 16-Module 03-Lesson 01_Basic SQL/01. Introduction-Z8WNfx9Oq9s.pt-BR.vtt
1.6 kB
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.es-ES.vtt
1.6 kB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-Vp43h6ZRyoQ.ar.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/09. Pandas Axis Names-8vr8KQuJLcQ.ar.vtt
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Part 11-Module 01-Lesson 13_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.en.vtt
1.6 kB
Part 13-Module 01-Lesson 07_Narrative Structures/23. Analyzing Narrative Structures-xgm7DYBijo0.ar.vtt
1.6 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example-Ae_UOATWmDM.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/09. Pandas Axis Names-8vr8KQuJLcQ.ar.vtt
1.6 kB
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-BngCW1fjvFk.ko.vtt
1.6 kB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites-0ANDJ8i_deE.zh-CN.vtt
1.6 kB
Part 13-Module 01-Lesson 07_Narrative Structures/15. One Human Heartbeat-unKu-dmor2w.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-t0iflCpBUDA.zh-CN.vtt
1.6 kB
Part 11-Module 01-Lesson 08_Outliers/08. Outliers Mini-Project Video-GRN0Whyy4Lk.pt-BR.vtt
1.6 kB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/27. Empirical Variability Bootstrapping-FvtAeWdzy4k.zh-CN.vtt
1.6 kB
Part 18-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -BS_p9kwMEMk.ar.vtt
1.6 kB
Part 05-Module 01-Lesson 05_Data Quality/13. Auditing Accuracy-mADDYP7ldl4.zh-CN.vtt
1.6 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.pt-BR.vtt
1.6 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/21. Duration vs. Exposure Example-993P7ivCrnQ.zh-CN.vtt
1.6 kB
Part 16-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling And EDA-EQXfxbUup0o.pt-BR.vtt
1.6 kB
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.th.vtt
1.6 kB
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-NXbR9GQbtnk.zh-CN.vtt
1.6 kB
Part 11-Module 01-Lesson 13_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.pt-BR.vtt
1.6 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-Fkm7ogOussQ.en.vtt
1.6 kB
Part 21-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.pt-BR.vtt
1.6 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/08. Darts-fSj1dwh7Kxc.zh-CN.vtt
1.6 kB
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.en.vtt
1.6 kB
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-HyjBus7S2gY.pt-BR.vtt
1.6 kB
Part 13-Module 01-Lesson 04_Design Principles/50. Grammar of Graphics and D3 Functions-rADl_md-WNM.pt-BR.vtt
1.6 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/06. 5 Number Summary to Variance-Ljhau0hrZ1g.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-BngCW1fjvFk.pt-BR.vtt
1.6 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 1-APRpwqFpGwI.pt-BR.vtt
1.6 kB
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.ja.vtt
1.6 kB
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.pt-BR.vtt
1.6 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/08. Continuous vs. Discrete Data-BzgZebZD9kk.en.vtt
1.6 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-8_SBvU8NYak.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-8_SBvU8NYak.zh-CN.vtt
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Part 05-Module 01-Lesson 05_Data Quality/16. Auditing Consistency-bCAkWxApvQM.zh-CN.vtt
1.6 kB
Part 17-Module 01-Lesson 11_Confidence Intervals/07. Confidence Intervals Applications-C0wgmeRx9yE.en.vtt
1.6 kB
Part 13-Module 01-Lesson 07_Narrative Structures/05. The Difficulty of Data Visualization-xzo96P5BwSI.zh-CN.vtt
1.6 kB
Part 21-Module 01-Lesson 03_Control Flow/02. Indentation-G8qUNOTHtrM.ar.vtt
1.6 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.pt-BR.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5-ONwh_Dcd6j8.pt-BR.vtt
1.6 kB
Part 09-Module 01-Lesson 01_What is EDA/07. Our Approach for This Course-dBsf-szQ00s.en.vtt
1.6 kB
Part 03-Module 01-Lesson 08_L3 Central Tendency/18. UNC-Ko-g24l1LpQ.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-KFVdS328iC8.ar.vtt
1.6 kB
Part 13-Module 01-Lesson 04_Design Principles/04. Chart Types-0a5oJR6TwAs.en.vtt
1.6 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/24. MM CLT-IAVgtiZLlOg.zh-CN.vtt
1.6 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-CuMPjPESfY0.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-pxaXkCjukGM.ar.vtt
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Part 12-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability-pDELcPTP2BI.en.vtt
1.6 kB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/08. Hierarchies with Trina-ys8Cn0o5gNI.zh-CN.vtt
1.6 kB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/03. Hierarchies with Trina-ys8Cn0o5gNI.zh-CN.vtt
1.6 kB
Part 03-Module 01-Lesson 20_L8 Estimation/20. Hypothesis Testing Song-ER5AITzr77g.zh-CN.vtt
1.6 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.ja.vtt
1.6 kB
Part 13-Module 01-Lesson 02_D3 Building Blocks/35. Visualization and D3 Basics-ueKb1OghNEU.en.vtt
1.6 kB
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.pt-BR.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/02. Why Do We Use Data Visualizations-iiOP4PE46f4.pt-BR.vtt
1.6 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/21. Sampling Observations-PsRMReOqccg.zh-CN.vtt
1.6 kB
Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-cwjvMYPB1Fk.ar.vtt
1.6 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/07. Loading Data into a DataFrame-N66_j0gxuhg.pt-BR.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/03. Choose Your Own Adventure-Ka9nwD0QzTI.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/35. Summary of the Update Function-IVmBlMgErzY.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/01. Introduction to Conditional Probability-Ok8948Wcbmo.zh-CN.vtt
1.6 kB
Part 17-Module 01-Lesson 14_Regression/04. Introduction to Linear Regression-RD4zbBvXDnM.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/07. Loading Data into a DataFrame-N66_j0gxuhg.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy-m989etSymQQ.ar.vtt
1.6 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/16. Pandas Series apply()-lhcl1UjM_0Q.en.vtt
1.6 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/17. Pandas Series apply()-lhcl1UjM_0Q.en.vtt
1.6 kB
Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error-FpeMuGuo74k.pt-BR.vtt
1.6 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-n0lluEhKUfQ.en.vtt
1.6 kB
Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-QBaNltqVj_0.ar.vtt
1.6 kB
Part 13-Module 01-Lesson 04_Design Principles/52. The Purpose of the Grammar of Graphics-pZyrfzuB5FE.pt-BR.vtt
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Part 17-Module 01-Lesson 13_Case Study AB tests/16. Drawing Conclusions-s-4ghG9vrGQ.pt-BR.vtt
1.6 kB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/23. Rent - t-Critical Values-0tcbCIrJGlM.pt-BR.vtt
1.6 kB
Part 17-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.pt-BR.vtt
1.6 kB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/03. Meal Prices-gzu9UcNF0_k.pt-BR.vtt
1.6 kB
Part 13-Module 01-Lesson 04_Design Principles/08. Unemployment Line Plot-EbD9ufptNd0.en.vtt
1.6 kB
Part 16-Module 03-Lesson 03_SQL Aggregations/02. NULLs-WYUkLKn6XCw.ar.vtt
1.6 kB
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.es-ES.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-_Z4d6-d-glM.zh-CN.vtt
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Part 12-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability-pDELcPTP2BI.pt-BR.vtt
1.6 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/32. Enter Update Exit-lmDLMOPOj5I.ar.vtt
1.6 kB
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.ja.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-_Z4d6-d-glM.zh-CN.vtt
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Part 12-Module 01-Lesson 02_Practice Behavioral Questions/05. What Motivates You at the Workplace-Aa9SFwiRbho.pt-BR.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/04. Test Cases-7CNatJ7PqZ4.en-US.vtt
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Part 12-Module 01-Lesson 01_Ace Your Interview/01. Introduction-pg4HUMgKLxI.zh-CN.vtt
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/02. Shortest Path Problem-huKUM97Vve8.en-US.vtt
1.6 kB
Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-pX849ta6kaI.pt-BR.vtt
1.6 kB
Part 13-Module 01-Lesson 07_Narrative Structures/26. Thinking with Joins-HGQ25_ivLMQ.pt-BR.vtt
1.6 kB
Part 19-Module 01-Lesson 02_Design/14. Designing for Color Blindness-k4iTzS7t2U4.zh-CN.vtt
1.6 kB
Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.en.vtt
1.6 kB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.en.vtt
1.6 kB
Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Ilu1JjjAbwA.en.vtt
1.6 kB
Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-LwazT9KH76w.ar.vtt
1.6 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations-q5PjL9GkVtM.en.vtt
1.6 kB
Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.zh-CN.vtt
1.6 kB
Part 12-Module 02-Lesson 08_Technical Interview - Python/04. Test Cases-7CNatJ7PqZ4.en.vtt
1.6 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/13. Explanatory vs Exploratory-SHq_zbB4ITo.pt-BR.vtt
1.6 kB
Part 18-Module 02-Lesson 01_Gathering Data/17. JSON Files In Python-8JdUknZP59Q.zh-CN.vtt
1.6 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations-q5PjL9GkVtM.en.vtt
1.6 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-Hv58aHpWvEE.ar.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-P6ZOr7JiMLk.zh-CN.vtt
1.6 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-MV_e0z9kFjM.zh-CN.vtt
1.6 kB
Part 12-Module 02-Lesson 02_List-Based Collections/01. Welcome to Collections-cZORvZq-tI0.zh-CN.vtt
1.6 kB
Part 12-Module 02-Lesson 04_Maps and Hashing/08. Hash Maps-A-ahUVi8pYQ.pt-BR.vtt
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/02. Shortest Path Problem-huKUM97Vve8.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/04. Features and Labels Musical Example-rnv0-lG9yKU.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/08. Source Scraping Webpages-ZqTad6Usf9g.zh-CN.vtt
1.6 kB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/05. Cohen's d-5rXOy1S5bVk.pt-BR.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/13. Mu-GXY-iMfZTn0.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-T_LpzJl-EVE.pt-BR.vtt
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Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-E63RZli2F2o.en-US.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/17. Performance Tuning 3-hIAE8W6x5O8.en.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/20. Conclusion -d_nKtLo5WYA.zh-CN.vtt
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components-DVvLiKedRw4.es-MX.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-eZ_yCrh4740.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Programmatic Data Cleaning Process-9-T1CFuOqdQ.en.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/12. Unpopular-FQoVv3o8vQg.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-T_LpzJl-EVE.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.ar.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/30. Rent - Increase n-UUn6ETq08SU.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/12. Plot Colors for Qualitative Factors-2ZVGl6LrOPw.pt-BR.vtt
1.6 kB
Part 13-Module 01-Lesson 04_Design Principles/09. Chart Suggestions-5V109AVr_JE.pt-BR.vtt
1.6 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/16. Establishing Statistical Significance-C22VZ_mY5RM.ar.vtt
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Part 15-Module 01-Lesson 02_Design Principles/01. Introduction-Q0lZkNF6O0g.en.vtt
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Part 19-Module 01-Lesson 02_Design/01. Introduction-Q0lZkNF6O0g.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/30. Hot Beverage-0O_5vNJycJg.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/40. Notation for Difference-r1X81SXRLKI.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots-AtmfksGs-0I.ar.vtt
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Part 21-Module 01-Lesson 04_Functions/01. Introduction-p5L4rTV1Pgk.pt-BR.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/11. Z-1MZnEo0UVX4.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-Hb2q-o4ElV4.zh-CN.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-XUZIGbX3JIg.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-hS7cpq-sOeQ.pt-BR.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/17. Why Data Dashboards-8ni2lCqAVvQ.ar.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/22. Conduct Hypothesis Test-HTuI3iFzOdU.zh-CN.vtt
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Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-E63RZli2F2o.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-kWsDkFkEjNM.pt-BR.vtt
1.5 kB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Statement-DRmkKVhe6-s.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.es.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/15. Getting Data from First Week -iT1vtUy2utg.pt-BR.vtt
1.5 kB
Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-GUD6yl0A1Aw.pt-BR.vtt
1.5 kB
Part 11-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection-S-xe0-XNo4I.pt-BR.vtt
1.5 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score-1V7JzqCfe9o.en.vtt
1.5 kB
Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/15. One Human Heartbeat-unKu-dmor2w.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-zxeKDuSK31M.pt-BR.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/22. in Operator-8iX-7hwKX1Q.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-mIBKd-JBnXY.es.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-NRCs22HJ-vI.pt-BR.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/24. all Operator-B3iYl-2HSXI.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-OT2aD9XgOWg.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-OT2aD9XgOWg.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/13. Match Boxplots-imNv6Q8GiQM.pt-BR.vtt
1.5 kB
Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-BRL0ZuvBm0U.pt-BR.vtt
1.5 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/21. Best Practices for Scraping-97FYi0SQFQ8.pt-BR.vtt
1.5 kB
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.en.vtt
1.5 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 1-APRpwqFpGwI.zh-CN.vtt
1.5 kB
Part 17-Module 01-Lesson 04_Probability/19. Probability Conclusion-dsVKoXymYDU.en.vtt
1.5 kB
Part 05-Module 02-Lesson 03_Elements of SQL/07. The One Thing SQL is Terrible At-wrjCB1abNyM.en.vtt
1.5 kB
Part 07-Module 01-Lesson 01_GitHub Review/08. Writing READMEs with Walter-DQEfT2Zq5_o.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.en.vtt
1.5 kB
Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-X_AS8NBngsk.zh-CN.vtt
1.5 kB
Part 17-Module 01-Lesson 16_Logistic Regression/31. Final Thoughts On Shifting To Machine Learning-YkZFjZ3Fx8A.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/21. Be Happy and Get Rid of Negatives-_afLozDIcLw.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/16. Pandas Series apply()-lhcl1UjM_0Q.pt-BR.vtt
1.5 kB
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-VBs6D4ggnYY.en.vtt
1.5 kB
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/32. Reducing Uncertainty-zuFMhmKQ--o.pt-BR.vtt
1.5 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/17. Pandas Series apply()-lhcl1UjM_0Q.pt-BR.vtt
1.5 kB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-3kH4ei9l4h8.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.en-US.vtt
1.5 kB
Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-2ieszOqnpWs.zh-CN.vtt
1.5 kB
Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.ar.vtt
1.5 kB
Part 14-Module 01-Lesson 01_Overview of AB Testing/21. Size vs. Power Trade-Off-bnTIVGBkKhM.en.vtt
1.5 kB
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.hr.vtt
1.5 kB
Part 03-Module 01-Lesson 11_L4 Variability/10. IQR-d7J0y_PSP2I.en.vtt
1.5 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/29. Decision Errors-TJ_p0xBI9bI.en.vtt
1.5 kB
Part 04-Module 02-Lesson 01_Data Analysis Process/27. Communication-P36LwI-R2Vw.zh-CN.vtt
1.5 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-mZgPfxFOFRE.ja.vtt
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Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-0QiU3p8POHk.ar.vtt
1.5 kB
Part 13-Module 01-Lesson 08_Animation and Interaction/04. Iterative Process-m2qDeWrGIDI.zh-CN.vtt
1.5 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/17. Performance Tuning 3-hIAE8W6x5O8.pt-BR.vtt
1.5 kB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Intro -FnUrE4dhgh8.zh-CN.vtt
1.5 kB
Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.ja.vtt
1.5 kB
Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-7HMAtB-342I.pt-BR.vtt
1.5 kB
Part 13-Module 01-Lesson 05_Dimple.js/27. Bar Chart The Bad-FCapLzYUQSo.zh-CN.vtt
1.5 kB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/06. Subqueries Part II-jko-RrZd0R8.zh-CN.vtt
1.5 kB
Part 11-Module 01-Lesson 12_Feature Selection/08. Features != Information-GOrv8faKHV4.pt-BR.vtt
1.5 kB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/33. Probability of Obtaining Mean--boAkUs-amM.pt-BR.vtt
1.5 kB
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-E63RZli2F2o.pt-BR.vtt
1.5 kB
Part 13-Module 01-Lesson 04_Design Principles/52. The Purpose of the Grammar of Graphics-pZyrfzuB5FE.en.vtt
1.5 kB
Part 13-Module 01-Lesson 07_Narrative Structures/59. New Data Stories in the Graphic-9yKFn_R2c_U.ar.vtt
1.5 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/07. Significance-FGtU7YDLX2Y.en.vtt
1.5 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/13. Explanatory vs Exploratory-SHq_zbB4ITo.en.vtt
1.5 kB
Part 16-Module 03-Lesson 01_Basic SQL/03. Entity Relationship Diagrams-YY2TAJLEINA.ar.vtt
1.5 kB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/06. r^2-X5F1reyQ_5U.pt-BR.vtt
1.5 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/30. Hot Beverage-0O_5vNJycJg.en.vtt
1.5 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/15. Experiment Design and Sizing Overview-6_odiPIKZO0.en.vtt
1.5 kB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/01. Introduction to Multiple Linear Regression-b26v8HK-8-o.pt-BR.vtt
1.5 kB
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.ja.vtt
1.5 kB
Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-VkQwfVQ00EQ.zh-CN.vtt
1.5 kB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-QII0tSAIex0.en.vtt
1.5 kB
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.en.vtt
1.5 kB
Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bgyN3RO2ICo.pt-BR.vtt
1.5 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-kWsDkFkEjNM.en.vtt
1.5 kB
Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bgyN3RO2ICo.pt-BR.vtt
1.5 kB
Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-sbQXPn9xLvI.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-q46nO0mznXM.zh-CN.vtt
1.5 kB
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.ar.vtt
1.5 kB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/19. What is Notation-MaHV5cKfcmE.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Programmatic Data Cleaning Process-9-T1CFuOqdQ.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.es-ES.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.es-ES.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends-19ZQP5wzmKA.pt-BR.vtt
1.5 kB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/21. Best Practices for Scraping-97FYi0SQFQ8.en-US.vtt
1.5 kB
Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-7HMAtB-342I.en.vtt
1.5 kB
Part 12-Module 01-Lesson 01_Ace Your Interview/01. Introduction-pg4HUMgKLxI.pt-BR.vtt
1.5 kB
Part 16-Module 03-Lesson 01_Basic SQL/09. Types Of Statements-vLvJbIz94C4.en.vtt
1.5 kB
Part 18-Module 02-Lesson 01_Gathering Data/22. Types Of Statements-vLvJbIz94C4.en.vtt
1.5 kB
Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-nsG26Dz9z44.zh-CN.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/05. Cohen's d-5rXOy1S5bVk.en.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/21. Best Practices for Scraping-97FYi0SQFQ8.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-7lKhG9bIMhs.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/27. Results from Sample-ypIyvJyZAs8.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-e6pJfNbQEKk.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/12. Data-d7aERRVkccY.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/12. Data-d7aERRVkccY.es.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-mIBKd-JBnXY.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/32. SD Social Networkers-R6KT9-ZbQ4c.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI-L_JV4fbRAfA.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/15. Getting Data from First Week -iT1vtUy2utg.en.vtt
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Part 11-Module 01-Lesson 01_Welcome to Machine Learning/03. Introduction Pt. III-0ZuxGhiqo5U.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-UNqgFhKvCL4.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. 141 Assess Intro V4-mdrAdtziXh4.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-4hoT_su75AQ.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.ar.vtt
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Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.pt-BR.vtt
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Part 09-Module 01-Lesson 02_R Basics/16. Advice for Data Scientists-FdkhUOtHIFg.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.ja.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=-J9FWaCBXhIk.ar.vtt
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Part 11-Module 01-Lesson 08_Outliers/08. Outliers Mini-Project Video-GRN0Whyy4Lk.en.vtt
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Part 12-Module 01-Lesson 01_Ace Your Interview/01. Introduction-pg4HUMgKLxI.es-MX.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/20. The Martini Glass-h8b8SOsSiT4.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=-J9FWaCBXhIk.ar.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-e6pJfNbQEKk.en-US.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-GTLvqNrAETc.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.pt-BR.vtt
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Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-HyjBus7S2gY.en.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/22. Outliers Advice-BhhDoTgYQmI.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/12. Affect t-Statistic-HMfd6rQrI0Y.pt-BR.vtt
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Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-qHk-FRWnYAo.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bgyN3RO2ICo.en.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bgyN3RO2ICo.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-32WHsQi1UWc.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/30. Filtering-vXGDYzAo22Y.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/32. Reducing Uncertainty-zuFMhmKQ--o.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-iu6CxSkq-wg.zh-CN.vtt
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/02. Tableau Desktop Download-End96VkLQc4.en.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/02. Tableau Desktop Download-End96VkLQc4.en.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-ncFtwW5urHk.pt-BR.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.pt-BR.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score-6kdmc3iTf78.zh-CN.vtt
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Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.zh-CN.vtt
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Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-8ZvLpWDITn4.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/13. Adding an Axis with Dimple-7okDT6V9Mmk.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-31yCnTUNzts.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/44. Parsing Overview and Parsing Attendance-_tVC3JuW7to.zh-CN.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/37. IN Operator-_JPO7wwX3uA.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/13. One-Sample t-Test-IdP9Ps2tHgw.zh-CN.vtt
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Part 17-Module 01-Lesson 14_Regression/08. Correlation Coefficients-rL5Bn8Fi-zE.zh-CN.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/11. Correlation Coefficients-rL5Bn8Fi-zE.zh-CN.vtt
1.5 kB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/07. Loading Data into a DataFrame-N66_j0gxuhg.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/12. Plot Colors for Qualitative Factors-2ZVGl6LrOPw.en.vtt
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Part 11-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit-VkUpuABChT4.pt-BR.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment -YrX-oiFilyA.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/07. Loading Data into a DataFrame-N66_j0gxuhg.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/18. Debugging Data Analysis Code -ReoDup994zk.ar.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-L9-lBQbknp0.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-zxnijlBCSpE.en-US.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-n7v-y8UrVJ0.ar.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/19. Adding the Series and Drawing the Chart-2zcZXJzW0aw.en.vtt
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/14. COALESCE-86vgu-ECBCQ.en.vtt
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Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-zxnijlBCSpE.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance-QReeBef_7vM.zh-CN.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/03. Types of Effect-Size Measures-FWSS2VadyBg.zh-CN.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables-e8zSXnyskro.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/14. Adding a Series with Dimple-clyCsNwceP0.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/50. Grammar of Graphics and D3 Functions-rADl_md-WNM.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/60. Context for the Reader-_GkNEO9qeWI.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-Fkm7ogOussQ.pt-BR.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/17. Performance Tuning 3-hIAE8W6x5O8.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet II-M0qR7to1fl4.ar.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/25. Using Sampling Distribution-NUY4Qobhojg.pt-BR.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-GUD6yl0A1Aw.en.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2-elZCLxVvJrY.en.vtt
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components-DVvLiKedRw4.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.ja.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.ar.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys-mFPq74OMkKk.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/13. Nonlinear SVMs-6UgInp_gf1w.pt-BR.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/03. What is the Difference-I3tQvrCgNrQ.pt-BR.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.ja.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/09. Combining Data-7KICenO-lKc.ar.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/10. Calculate SDs-bjk5m0wrj3w.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-UMWsyRYnfPk.zh-CN.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/04. More Examples-gj-or8b8TmM.pt-BR.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces)-1y_qjUMDsCw.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-TSw2AAaKxBA.zh-CN.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/08. Extracting Data-OeiBJ_D-ZsM.zh-CN.vtt
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Part 11-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit-VkUpuABChT4.en.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/04. Further Motivation-sjGxUKrbKoI.en.vtt
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Part 11-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.zh-CN.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-nu2OKJwDvvE.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure-z_Gp9ttyiwg.pt-BR.vtt
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Percentiles-Qro8uvysnys.ar.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-_Lp_3KUltFk.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/45. The Grammar of Graphics-AdRbdZhLn04.zh-CN.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/12. Example Details-aR6Z7ggnjEY.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-hUmXWHOPxpI.zh-CN.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/09. Continuous Distribution-ytUY1_EfxPk.pt-BR.vtt
1.5 kB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/08. t-Table-lccjSiVTx7c.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/23. CI Bounds-T9VX2KvzJ-k.zh-CN.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/07. Anatomy of a Table-PhvA7DCgtpw.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.en.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-Nmf80xB1DN0.pt-BR.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-P1aYwQhPnPQ.pt-BR.vtt
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Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-ieiQqLicBjg.ja.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1-bFDJ_FstSZ4.pt-BR.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/01. SQL is for Elephants-BYAyquwZmdM.ar.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-N5T8ouw1SGc.ar.vtt
1.5 kB
Part 06-Module 01-Lesson 01_Working with MongoDB/21. Querying Arrays Using Scalars-8uhfnWgiBHM.zh-CN.vtt
1.5 kB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/33. What Happened-LOwWWIXvnhU.pt-BR.vtt
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Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-5zoL8YdM6sI.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-pX849ta6kaI.en.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/04. What is Data-ldTDAjrVsA8.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-C6okqt-jf08.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-QII0tSAIex0.ja.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.ar.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Introduction To Notation-ISkBSUVH49M.ar.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/15. Two Useful Theorems-jQ5i7CALdRQ.pt-BR.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/03. Fitting A Multiple Linear Regression Model-EZNvBF66_b0.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-C6okqt-jf08.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-095MTpItufM.en.vtt
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/09. Renaming Columns-3Oo4gUP2_Rw.pt-BR.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/24. There Must Be A Better Way-oBp8YX2AgJw.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.es-ES.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.zh-CN.vtt
1.5 kB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/06. r^2-X5F1reyQ_5U.en.vtt
1.5 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/08. Data Visualization and You-m_nSthII_IE.ar.vtt
1.5 kB
Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-pq31lSXEQl0.ar.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next-AwpX6HkhL0k.ar.vtt
1.5 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.ja.vtt
1.5 kB
Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-iCTPBcowJRY.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-CuMPjPESfY0.ja.vtt
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Part 12-Module 01-Lesson 02_Practice Behavioral Questions/05. What Motivates You at the Workplace-Aa9SFwiRbho.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-UjyPKvNHz4A.zh-CN.vtt
1.5 kB
Part 17-Module 01-Lesson 12_Hypothesis Testing/29. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.es-ES.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution-oERHYF9QCkY.pt-BR.vtt
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Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-N6hiygoT9FE.ar.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/24. all Operator-B3iYl-2HSXI.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ZhWxuf5czTA.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-TluBvgsphHQ.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data-D7m25cvqUpw.en.vtt
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Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.ar.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/07. The One Thing SQL is Terrible At-wrjCB1abNyM.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-lbNk216NW48.en.vtt
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/15. Sets and groups with Trina-I59eqlvfMZk.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.ar.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-lbNk216NW48.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.zh-CN.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results-l_HFnHve3Ok.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/15. Experiment Design and Sizing Overview-6_odiPIKZO0.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Lv22Usic4A8.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-k8Ru6RQJbd4.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/04. Picking the Most Suitable Metric-GAfPvj2SSiE.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-k8Ru6RQJbd4.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-jfGdUdo37Vk.pt-BR.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/18. Comparing Two Samples-kaVG7U0rda8.ar.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-lbNk216NW48.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-gBdKhmtrtG8.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/65. Lesson 3 Recap-MmJ6fBojjiA.ar.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-lbNk216NW48.pt-BR.vtt
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Part 19-Module 01-Lesson 02_Design/02. Lesson Overview-Gg77PqkQkhs.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.ja.vtt
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Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-MEtIAGKweXU.zh-CN.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-XqEQG4qo94I.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-KrZpJwPlSbA.zh-CN.vtt
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.es-MX.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate-eu1gO_76pSY.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/40. Jelly Beans-1HmiArFN-EI.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.pt-BR.vtt
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Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-ADNFKiAjmWA.ar.vtt
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Part 05-Module 01-Lesson 05_Data Quality/02. What is Data Cleaning-dzqOwmxK3j4.pt-BR.vtt
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Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.zh-CN.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/10. AVG-diqCDztOL64.en.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Background Of Bootstrapping-6Vg5kGoDl7k.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip Solution -Pzy8nHA_EJc.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/21. Storing Data-hcosH34b-yw.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-UXLEe6bNpM4.en.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/06. Example of Sampling Distributions - Part I-1XezzP6kxUE.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate-eu1gO_76pSY.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-sbQXPn9xLvI.ko.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-ZULplTNbIIs.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-L9-lBQbknp0.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.en.vtt
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Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.en.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/08. Hash Maps-A-ahUVi8pYQ.zh-CN.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-UXLEe6bNpM4.pt-BR.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/28. Conclusion-rrSNkPGJmTc.zh-CN.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-XqEQG4qo94I.en.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/04. COUNT-b4FCWAEGmLg.en.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/19. What is Notation-MaHV5cKfcmE.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/02. Alpha Levels-pjBOYFAkNME.en.vtt
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Part 09-Module 01-Lesson 01_What is EDA/07. Our Approach for This Course-dBsf-szQ00s.ja.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/18. Recreating China's Red Dot-tDRHSTivs4k.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/26. Sum of Squares-fktfjG1SnkI.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-ZULplTNbIIs.it.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-6BBUSWrSuFA.ar.vtt
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Part 12-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability-pDELcPTP2BI.zh-CN.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/12. Caution with Class Selections-fP30uBJljNk.zh-CN.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 2-CyeB16-eGSg.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.it.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/07. Javascript Debugger-AzbaV5CT9es.pt-BR.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/01. Introduction to Logistic Regression-P_f2RjjnPEg.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/09. HTML File Structure -4ef_Dr_SXTw.ar.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/02. Probability-oR8H9vdtreE.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-sS-lw3LxATY.pt-BR.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip Solution -Pzy8nHA_EJc.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-nqMT8qTmQPY.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.ar.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.en.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/16. GROUP BY Part II-0HQ-TshNNQA.pt-BR.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip Solution -Pzy8nHA_EJc.en.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-C6okqt-jf08.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-C6okqt-jf08.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/32. SD Social Networkers-R6KT9-ZbQ4c.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/07. Anatomy of a Table-PhvA7DCgtpw.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-P1aYwQhPnPQ.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/11. Data Vis in Data Science-e_-61K3jK1Y.zh-CN.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5-tEmdl6zhvgA.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-hS7cpq-sOeQ.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-SxCK2_82FfQ.pt-BR.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/27. WHERE with Non-Numeric Data-_pLx7MHOyjo.ar.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/23. Measures of Center-eNoE9hSDxPA.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-nqMT8qTmQPY.pt-BR.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/06. SUM-0zUP14PeiXk.ar.vtt
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Part 21-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.ar.vtt
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Part 09-Module 01-Lesson 02_R Basics/15. Data Munging-q_Ghc6VsDo0.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bgyN3RO2ICo.zh-CN.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bgyN3RO2ICo.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation-Mak839YmmrA.ja.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/01. Lesson Overview-k5T30IHD8T8.ar.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion-SRXNBlvW-xw.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/26. Thinking with Joins-HGQ25_ivLMQ.en.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Common Table Expressions-qtEKO7B8bXQ.en.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/09. Querying Using Field Selection-V2UMNT9VBrw.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.ar.vtt
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Part 11-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy-b-oE175NJiQ.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/01. Introduction-QXxtu_gdWQs.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/13. Nonlinear SVMs-6UgInp_gf1w.en.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.es-ES.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/02. Introduction-QXxtu_gdWQs.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-dkLEMSLTxvk.pt-BR.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-Nmf80xB1DN0.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=-rQivl4aJCOI.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/07. Intro To Stanley Terrain Classification-TwFhCeov85E.pt-BR.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/01. Introduction-aAmMK8tGEYc.zh-CN.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (Before Cleaning)-jJH3H8Rqv8s.pt-BR.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=-rQivl4aJCOI.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/29. Decision Errors-TJ_p0xBI9bI.zh-CN.vtt
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Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-HSeIrqW-YGw.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-97v0kEWjcmg.en.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Background Of Bootstrapping-6Vg5kGoDl7k.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/05. Approximate Margin of Error-P4gLGxQrKjY.zh-CN.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/22. Popular Chris-cRb2ONJAvog.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/09. What We Need to Compare the Means-y27MBpbnP48.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.ja.vtt
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Part 10-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-4Aj_qdImmGo.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/30. Standard Deviation-0seYYIPBXxI.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-m8d9J5w3axY.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/18. Critical Values of Z-_vKCQnll45c.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-cUDZ1vkmdnk.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-sS-lw3LxATY.en.vtt
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/15. Sets and groups with Trina-I59eqlvfMZk.en.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-NRCs22HJ-vI.en.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/11. Multiple Field Queries-tsAh4HonzIw.ar.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/01. Introduction to JOINs-YvZ010GU-Ck.zh-CN.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/15. Two Useful Theorems-jQ5i7CALdRQ.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/15. Calculating a Confidence Interval-T-QWVJtXHAs.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-sbQXPn9xLvI.it.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-GUD6yl0A1Aw.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation-Mak839YmmrA.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/40. Jelly Beans-1HmiArFN-EI.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-KuihzV_LLAE.zh-CN.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.ar.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/20. SD of Standardized Distribution-LuI1poHmFOw.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-BRL0ZuvBm0U.en.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Data in the Real World-HmipezTjTDY.zh-CN.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-ncFtwW5urHk.en.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-1lNAvDubBfI.ar.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-SxCK2_82FfQ.en.vtt
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Part 17-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.ja.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/01. Introduction to Multiple Linear Regression-b26v8HK-8-o.en.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.ar.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/06. Example of Sampling Distributions - Part I-1XezzP6kxUE.pt-BR.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/13. Dummy Variables Recap-r7Lek8rsIcg.zh-CN.vtt
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Part 21-Module 01-Lesson 01_Why Python Programming/03. L1 03 Programming In Python V4-O1cTNYAjeeg.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/21. Shape of Distribution When n Increases-kJ4Y8a1rOkY.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-TluBvgsphHQ.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Visual-PVbOzw5libM.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-kFKsCAyiPuY.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-kFKsCAyiPuY.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/06. Wide and Long Format-zlaeISxRESQ.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/30. Color Blind-mmw24xSEB3A.ar.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5-ONwh_Dcd6j8.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/15. Roll 1 Die-oJXYNArEk8k.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/11. SVM Decision Boundary-8hEjeR0qLnA.ja.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Subqueries Using WITH-IszTmDKyKHI.en.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/04. Further Motivation-sjGxUKrbKoI.zh-CN.vtt
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/09. Extra Practice With Dashboards-Va2zNfnUC6o.ar.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-buxApBhZCO0.ja.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/14. Confidence Intervals-fDkfHKODOcQ.ar.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Why Are Sampling Distributions Important-aDFDOCJKoH0.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-n0lluEhKUfQ.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/38. Naive Bayes Mini-Project Video-UH2oSijkszo.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/58. Juxtaposition and Comparison-abaD-wvlbkg.zh-CN.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value-6Z3BJWRuOAE.en.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/28. Variability Summary-sDejdrYe8cg.en.vtt
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Part 17-Module 01-Lesson 14_Regression/17. How Do We Know If Our Model Fits Well-0vPtPAqMHJE.zh-CN.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/02. Why Do We Use Data Visualizations-iiOP4PE46f4.en.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.pt-BR.vtt
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Part 11-Module 01-Lesson 14_Validation/15. Validation Mini-Project Video-dlbeMlRoFd4.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/25. You Can Iterate-QsJqoJYhTiw.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-BngCW1fjvFk.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-ZULplTNbIIs.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-PRQDaHphZhw.ar.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/02. Histograms-4t10RgUv2Fc.zh-CN.vtt
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Part 21-Module 01-Lesson 04_Functions/01. Introduction-p5L4rTV1Pgk.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-OT2aD9XgOWg.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-OT2aD9XgOWg.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/27. Klout Parameters-wV-6gQepmn0.zh-CN.vtt
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Part 09-Module 01-Lesson 02_R Basics/16. Advice for Data Scientists-FdkhUOtHIFg.ja.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.zh-CN.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/10. AVG-diqCDztOL64.pt-BR.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/02. Histograms-4t10RgUv2Fc.mp4
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Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds-WeS0ogG86nk.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-93y6ms_fuQQ.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-dkLEMSLTxvk.en.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-ClkOE3kdvLs.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data-vhl-SADfti8.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/10. NumPy Index Arrays-93y6ms_fuQQ.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.it.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Lv22Usic4A8.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/12. Affect t-Statistic-HMfd6rQrI0Y.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/32. Keyboards-bLDBg86nm6o.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-cUDZ1vkmdnk.pt-BR.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/16. GROUP BY Part II-0HQ-TshNNQA.en.vtt
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Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-ieiQqLicBjg.en.vtt
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Part 11-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy-b-oE175NJiQ.en-US.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts-i6nppkOcNoE.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-OT2aD9XgOWg.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-OT2aD9XgOWg.es.vtt
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Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-ieiQqLicBjg.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/15. Formula of Entropy-NHAatuG0T3Q.ja.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/50. Goodbye and Keep Learning-B4EKdtRmv60.zh-CN.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/07. How Databases Store Data-H0C9z_sRvLE.pt-BR.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/22. How Databases Store Data-H0C9z_sRvLE.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose-pBSQI8EmhvM.pt-BR.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling And EDA-EQXfxbUup0o.en.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/28. Show Me-Jpk99mgmwaA.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250-mPcWDYTRDs8.en.vtt
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Part 11-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.ja.vtt
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Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-HyjBus7S2gY.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro-rR68JXwKBxE.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/41. The World Cup Narrative-nnqZR2GdcAA.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/15. Problem with IQR-h5l2EP3DR-4.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/12. Generalize CI-7JS9PPQ6cN4.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/06. Estimating Your Audience Size-FfzVPWM5DZ8.ar.vtt
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Part 11-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy-b-oE175NJiQ.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/28. How Visualizations can Save Lives-VUllIatQ3tI.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/23. The Radius Scale-Rkrj1HjaMQM.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/01. Introduction to Probability-HeoQccoqfTk.ar.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 2-9YPOlROXNZM.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/35. What's Next-mKJkmv7h9ro.ar.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-1R44jvxIPJY.en.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/14. Correct Interpretations of Confidence Intervals-IhYv_SlN7e8.zh-CN.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/17. Find Standard Error-YNuoRW6EyEo.pt-BR.vtt
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Part 09-Module 01-Lesson 01_What is EDA/09. Course Overview-W8N0aSMPff8.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-Keh5GwaSWdk.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-DIrLvDqhjCg.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.th.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/01. Finding Stories-vVWFVaiWomw.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/28. Outlining the Update Function-k5ZZQ3ulwX4.zh-CN.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/10. Assessing Vs Exploring V2 -hVFZ6jFKOso.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample-9na_mOWP7pw.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/18. Better Sample-9na_mOWP7pw.zh-CN.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/09. How Does Project Submission Work-jCJa_VP6qgg.ar.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/08. Writing READMEs with Walter-DQEfT2Zq5_o.en.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/10. Integrity and Mindset-zCOr3O50gQM.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/07. Significance-FGtU7YDLX2Y.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/52. D3 Hides Complexity-iNXkYbkD3IU.ar.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-kT0jBsXOouw.pt-BR.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-T_LpzJl-EVE.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/24. Overfitting-plx_F2BkwNQ.ar.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/30. Hot Beverage-0O_5vNJycJg.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/12. DataFrame apply()-aGEUhSRys8w.ar.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Lv22Usic4A8.es.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.pt-BR.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/13. Line Plots-GsaBT47pjgQ.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-vxS-Kh4eI0U.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-sS-lw3LxATY.ja.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys-mFPq74OMkKk.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-M_8000Yz_DA.zh-CN.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/12. Plot Colors for Qualitative Factors-2ZVGl6LrOPw.zh-CN.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/04. Test Cases-7CNatJ7PqZ4.zh-CN.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Why Even Create Graphics - Data Visualization and D3.js-lqI3LFwMVUc.en.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/16. Operators-PlJ_dfdEbR0.ar.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-xPZOSx1q_dg.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/17. Pandas Series apply()-lhcl1UjM_0Q.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.ar.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/15. The Benefits of Dimple-PkCeV9KNiMg.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.ja.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.ar.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values--xVYQQHNNuM.ar.vtt
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Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-iCTPBcowJRY.zh-CN.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-UXLEe6bNpM4.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values--xVYQQHNNuM.ar.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/01. Introduction to Lesson 5-l2Nab0LY_cI.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-DIrLvDqhjCg.en.vtt
1.4 kB
Part 11-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection-S-xe0-XNo4I.zh-CN.vtt
1.4 kB
Part 17-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.es-ES.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-lEl0alktZkM.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-lEl0alktZkM.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/08. Aggregations-TE9uvPwvpu4.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose-pBSQI8EmhvM.en.vtt
1.3 kB
Part 11-Module 01-Lesson 12_Feature Selection/08. Features != Information-GOrv8faKHV4.zh-CN.vtt
1.3 kB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 3-oVGmi4zBOT8.ar.vtt
1.3 kB
Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-xJtmPbEfpFo.ar.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/09. Types Of Statements-vLvJbIz94C4.zh-CN.vtt
1.3 kB
Part 18-Module 02-Lesson 01_Gathering Data/22. Types Of Statements-vLvJbIz94C4.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/29. One Dimension-vsqelq1aYy8.pt-BR.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score-iHnjTqGPbVg.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.ar.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-JsFlZfNpVl4.pt-BR.vtt
1.3 kB
Part 13-Module 01-Lesson 07_Narrative Structures/37. Visualize Every Game of the World Cup-fxgnL-Lv684.ar.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/22. Outro -lfWT0kLfe8c.pt-BR.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/10. Theoretical Normal Distribution-vyy5yUt1IrE.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.zh-CN.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/10. Interview Wrap-Up-sz4Ekcu9a_Q.en-US.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-4Aj_qdImmGo.es.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs-Zw3X9BQQKB0.pt-BR.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/17. Why Data Dashboards-8ni2lCqAVvQ.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.ar.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/15. Why Even Create Graphics-lqI3LFwMVUc.pt-BR.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Why Even Create Graphics - Data Visualization and D3.js-lqI3LFwMVUc.pt-BR.vtt
1.3 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations-q5PjL9GkVtM.zh-CN.vtt
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Part 05-Module 01-Lesson 05_Data Quality/01. Introduction-JA7oIPaf9PM.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age-GFKRNBnFGVU.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.ar.vtt
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Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-4Fkfu37el_k.ar.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/10. Interview Wrap-Up-sz4Ekcu9a_Q.en.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/03. What Is Coming Up-oDJsnQcCPr4.ar.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations-q5PjL9GkVtM.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/02. One Number to Describe Data-6QfvhQ0En0E.pt-BR.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/10. Less than 240-xUkquw-73BY.zh-CN.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/12. Using the Z-Table-GF0qAvNKpOA.pt-BR.vtt
1.3 kB
Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-095MTpItufM.zh-CN.vtt
1.3 kB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/13. Explanatory vs Exploratory-SHq_zbB4ITo.zh-CN.vtt
1.3 kB
Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts-q-EjlMl1Bj4.pt-BR.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/13. Karma-cNFMJpVQlKY.en.vtt
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Part 11-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning-Xcb9jjjAm60.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age-GFKRNBnFGVU.ja.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-kWsDkFkEjNM.zh-CN.vtt
1.3 kB
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.zh-CN.vtt
1.3 kB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/10. 27. English Teaching-HmsNljRIsr4.pt-BR.vtt
1.3 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/11. In-Place vs. Not In-Place-STqN_v6Iz5o.en.vtt
1.3 kB
Part 09-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose-pBSQI8EmhvM.ja.vtt
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Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.zh-CN.vtt
1.3 kB
Part 11-Module 01-Lesson 04_Decision Trees/15. Formula of Entropy-NHAatuG0T3Q.en.vtt
1.3 kB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/03. What is the Difference-I3tQvrCgNrQ.en.vtt
1.3 kB
Part 21-Module 01-Lesson 03_Control Flow/02. Indentation-G8qUNOTHtrM.pt-BR.vtt
1.3 kB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place-STqN_v6Iz5o.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.es.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores-2OKqKX7DnMQ.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-P1aYwQhPnPQ.zh-CN.vtt
1.3 kB
Part 17-Module 01-Lesson 16_Logistic Regression/09. Model Diagnostics-XsYFAtzF6e4.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-BRL0ZuvBm0U.zh-Hans.vtt
1.3 kB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-kT0jBsXOouw.en.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-ncFtwW5urHk.zh-CN.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/07. Confidence Intervals Applications-C0wgmeRx9yE.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/30. Hot Beverage-r-TWqzDJZJs.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/01. Finding Stories-vVWFVaiWomw.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-4hoT_su75AQ.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-9JHRpVTMuK4.hi.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/15. One Human Heartbeat-unKu-dmor2w.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/26. Thinking with Joins-HGQ25_ivLMQ.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-OT2aD9XgOWg.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-OT2aD9XgOWg.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/15. Bigger Sample, Smaller CI-DRarpjC23kc.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/05. DF - Add to 10-mb1eR8nb9t4.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.pt-BR.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 2-9YPOlROXNZM.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-uSXJtEpwEVM.pt-BR.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma-NMnlSnu8DPI.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/02. What to Do First-TgAIx_NFaD8.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/01. Animation and Interaction-4aBXHspd7WI.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/16. Roll 2 Dice-OVeEr0CSe8U.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/02. Alpha Levels-pjBOYFAkNME.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-BHFxJmzw1gY.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/03. Meal Prices-gzu9UcNF0_k.en.vtt
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Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3--XfG5hXveiE.pt-BR.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/21. Size vs. Power Trade-Off-bnTIVGBkKhM.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-QX_KFUXtHkw.pt-BR.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-QX_KFUXtHkw.pt-BR.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2-elZCLxVvJrY.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.pt-BR.vtt
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Part 12-Module 01-Lesson 04_Land a Job Offer/01. Land a Job Offer-ZQJoT8QL_hw.en.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/01. Introduction-Z8WNfx9Oq9s.zh-CN.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Why the Standard Deviation-XlTBvjQ2t8w.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1-bFDJ_FstSZ4.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/15. Getting Data from First Week -iT1vtUy2utg.zh-CN.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6-eqFgLu0eqBE.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/47. Start Creating-Nr1w-Hxjld4.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/19. Randomness-KwmQDhUkLAE.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/19. Randomness-KwmQDhUkLAE.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/11. In-Place vs. Not In-Place-TVyv8acRPrs.en.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-Uf_KdjVT2Xg.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/35. Visualization and D3 Basics-ueKb1OghNEU.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.pt-BR.vtt
1.3 kB
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-Uf_KdjVT2Xg.pt-BR.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place-TVyv8acRPrs.en.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/25. Welcome to the End of Evaluation Lesson-sgFfl-j_oCs.ar.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/37. IN Operator-_JPO7wwX3uA.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-buxApBhZCO0.en.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/01. Lesson Introduction-nQBbywNKTVc.ar.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/19. DISTINCT-YDJEHkgKORY.en.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/10. Integrity and Mindset-zCOr3O50gQM.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-mIn7nMR092Q.ar.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/16. Establishing Statistical Significance-C22VZ_mY5RM.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-mIn7nMR092Q.ar.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-ZULplTNbIIs.zh-Hans.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-cUDZ1vkmdnk.zh-CN.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/22. Outliers Advice-BhhDoTgYQmI.zh-CN.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/12. Unpopular-FQoVv3o8vQg.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.en.vtt
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Part 11-Module 01-Lesson 08_Outliers/08. Outliers Mini-Project Video-GRN0Whyy4Lk.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.pt-BR.vtt
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Part 17-Module 01-Lesson 13_Case Study AB tests/09. Experiment II-fq4eO7CybA4.pt-BR.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-vfEi3aOawTI.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/10. Dimple Axes, Series and Fields-nSqsoDChbEU.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/12. Data-d7aERRVkccY.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/12. Data-d7aERRVkccY.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.ja.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.es-ES.vtt
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Part 11-Module 01-Lesson 13_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-aznzJPXavDg.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.en.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/14. Other Sampling Distributions-Bxl0DonzX8c.pt-BR.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/05. Cohen's d-5rXOy1S5bVk.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots-AtmfksGs-0I.pt-BR.vtt
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Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-rNR4_JqCEuk.en.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/14. Performance Tuning Motivation-aY4_uYWEuoE.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/17. Plotting in Pandas-ujJShz9YfAU.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-sS-lw3LxATY.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-Keh5GwaSWdk.en.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.it.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/18. Plotting in Pandas-ujJShz9YfAU.pt-BR.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular-W5qXCZ-nrHM.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/13. Nonlinear SVMs-6UgInp_gf1w.zh-CN.vtt
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Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-5j6VZr8sHo8.pt-BR.vtt
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Part 11-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit-VkUpuABChT4.zh-CN.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/19. DISTINCT-YDJEHkgKORY.pt-BR.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/04. What is Data-ldTDAjrVsA8.en.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/27. Conclusion-IanoSiET2nA.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-BRL0ZuvBm0U.zh-TW.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/07. How Databases Store Data-H0C9z_sRvLE.en.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/22. How Databases Store Data-H0C9z_sRvLE.en.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-C6okqt-jf08.zh-CN.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-C6okqt-jf08.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-NRCs22HJ-vI.zh-CN.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/11. Report Results Effect Size-jjByXJIiCLs.pt-BR.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/24. all Operator-B3iYl-2HSXI.zh-CN.vtt
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Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3--XfG5hXveiE.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-8IzQG_2WAcs.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.en.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/03. Projects and Progress-Z9ZLMQWsbsk.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/25. Changing Bin Size-fI_SYnWB1XA.pt-BR.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/12. Using the Z-Table-GF0qAvNKpOA.en.vtt
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Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-gg7SAMMl4kM.pt-BR.vtt
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/02. Shortest Path Problem-huKUM97Vve8.zh-CN.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ZhWxuf5czTA.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.zh-CN.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Notation Parameters vs. Statistics-webref_dLrA.zh-CN.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/27. WHERE with Non-Numeric Data-_pLx7MHOyjo.pt-BR.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/04. COUNT-b4FCWAEGmLg.zh-CN.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.es-ES.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics-meNSO42JF6I.ar.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-TU63rBOwXQ8.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/26. Evaluation Mini-Project Video-s13K9G1VaWM.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-KhGfaSWoEn0.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.ja.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 -Ngl_TsqhMsc.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-sbQXPn9xLvI.en.vtt
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Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.en.vtt
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Part 17-Module 01-Lesson 04_Probability/19. Probability Conclusion-dsVKoXymYDU.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-e6pJfNbQEKk.zh-CN.vtt
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Part 11-Module 01-Lesson 16_Tying It All Together/03. End of Content-MFRkl-aXL8I.ar.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean-DM1zSW5aoCc.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/11. Slope and Intercept-Ksn1g5fCe1I.ar.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/16. Establishing Statistical Significance-C22VZ_mY5RM.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/27. Making Decisions about Uncertain Data-GM8MV0FvCUo.ar.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/09. What We Need to Compare the Means-y27MBpbnP48.zh-CN.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/18. Hypotheses-FDcgsIOTv94.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.ar.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/03. Choose Your Own Adventure-Ka9nwD0QzTI.pt-BR.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-eZ_yCrh4740.zh-CN.vtt
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Part 17-Module 01-Lesson 13_Case Study AB tests/16. Drawing Conclusions-s-4ghG9vrGQ.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-PXNaLWJ5SKg.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/24. Final Thoughts-CNGDocH1k3k.ar.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-rGw4xFsUUqE.en.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/25. Conclusion-YS4bR1vQ3Ls.ar.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.ar.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces)-1y_qjUMDsCw.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/27. Conclusion-IanoSiET2nA.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-ZO7y9tsSQ0A.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.en-GB.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends-19ZQP5wzmKA.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/25. Using Sampling Distribution-NUY4Qobhojg.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/07. Anatomy of a Table-PhvA7DCgtpw.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-K-rQ8KnmmH8.ar.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/03. Confirming Inputs-8lPTOG1yLsg.en-US.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/09. The Data Science Process-Kxp2TNV3n5k.ar.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling And EDA-EQXfxbUup0o.zh-CN.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/08. Aggregations-TE9uvPwvpu4.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-sy_jiSEy-Nw.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts-q-EjlMl1Bj4.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-Vx9bxJHQJf8.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-Vx9bxJHQJf8.es.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/32. Keyboards-bLDBg86nm6o.en.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-7HMAtB-342I.zh-CN.vtt
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/21. 37. Insomnia-HbnB5SQqmoM.pt-BR.vtt
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Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.pt-BR.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/03. Confirming Inputs-8lPTOG1yLsg.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/23. Analyzing Narrative Structures-xgm7DYBijo0.pt-BR.vtt
1.3 kB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/12. Affect t-Statistic-c6vE21UVksU.zh-CN.vtt
1.3 kB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-si8AcC5pTfM.ar.vtt
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Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-DIrLvDqhjCg.zh-CN.vtt
1.3 kB
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.pt-BR.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-si8AcC5pTfM.ar.vtt
1.3 kB
Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-rNR4_JqCEuk.zh-CN.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/02. Technical Interlude-QWA06Ro4ix0.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/40. Notation for Difference-r1X81SXRLKI.zh-CN.vtt
1.3 kB
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.ar.vtt
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Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.zh-CN.vtt
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/09. Renaming Columns-3Oo4gUP2_Rw.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/06. Wide and Long Format-zlaeISxRESQ.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-jfGdUdo37Vk.zh-CN.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/15. Experiment Design and Sizing Overview-6_odiPIKZO0.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-zxeKDuSK31M.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.it.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/32. Keyboards-0m5k7Ni1O48.en.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/02. Technical Interlude-QWA06Ro4ix0.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/09. Chart Suggestions-5V109AVr_JE.zh-CN.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1 Solution -Noykh9Zt6aI.ar.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-_c_chcNiHyo.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/21. Linear Regression Errors-A4nPMEOcUd4.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/54. Use Variables Wisely-j8o2WUo3-Xg.ar.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 2-CyeB16-eGSg.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/10. IQR-d7J0y_PSP2I.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/21. Be Happy and Get Rid of Negatives-_ULZYGI6LPQ.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/05. Visualizations in Data Science-UCKGGQ4LFjo.pt-BR.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 -Ngl_TsqhMsc.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings-0-LYyC_70jk.pt-BR.vtt
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Part 09-Module 01-Lesson 01_What is EDA/07. Our Approach for This Course-dBsf-szQ00s.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-8QEAYYIyopY.ar.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/33. Adding Bars and Text-EcwO8YPrn-M.en.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-8QEAYYIyopY.ar.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs-Zw3X9BQQKB0.en.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-QCakJ5gxF5w.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-L9-lBQbknp0.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-VBs6D4ggnYY.zh-CN.vtt
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Part 12-Module 02-Lesson 05_Trees/13. BST Complications-pcB0wV7myy4.pt-BR.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next-AwpX6HkhL0k.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-lbNk216NW48.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.ar.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/28. Show Me-Jpk99mgmwaA.en.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-lbNk216NW48.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-zxnijlBCSpE.zh-CN.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution-oERHYF9QCkY.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-AO8vSyAtfV4.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.ar.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/02. Why Do We Use Data Visualizations-iiOP4PE46f4.zh-CN.vtt
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Part 11-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy-b-oE175NJiQ.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 2-CyeB16-eGSg.zh-CN.vtt
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Part 21-Module 01-Lesson 04_Functions/01. Introduction-p5L4rTV1Pgk.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys-mFPq74OMkKk.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/02. What to Do First-TgAIx_NFaD8.ja.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Tp5WCAJiCRY.pt-BR.vtt
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/21. 37. Insomnia-HbnB5SQqmoM.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error-FpeMuGuo74k.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.es-AR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/33. What Happened-LOwWWIXvnhU.en.vtt
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Part 11-Module 01-Lesson 03_SVM/11. SVM Decision Boundary-8hEjeR0qLnA.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-FLpXmoHp7eE.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-3nZ2FL7C3sU.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-JsFlZfNpVl4.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/33. Advantages with CSS-lCTey7ryZ1A.ar.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-FLpXmoHp7eE.zh-CN.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2-cpDTPUNDo4U.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-aznzJPXavDg.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.ar.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/03. Choose Your Own Adventure-Ka9nwD0QzTI.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/21. Linear Regression Errors-A4nPMEOcUd4.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.en.vtt
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/21. 37. Insomnia-HbnB5SQqmoM.es.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/13. Karma-cNFMJpVQlKY.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-LwazT9KH76w.pt-BR.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Common Table Expressions-qtEKO7B8bXQ.zh-CN.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/04. Manual Vs Programmatic Cleaning -AQFBVQy_HyY.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-ZULplTNbIIs.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/22. Find P-Value-pwQ7IQgremk.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/33. Probability of Obtaining Mean--boAkUs-amM.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.nl.vtt
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Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-n1EbdV_CTcc.ar.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.pt-BR.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. 141 Assess Intro V4-mdrAdtziXh4.pt-BR.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/35. L2 01 Compound Data Structures V1-jmQ8IKvQgBU.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-HVa4G8jQbEo.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-HVa4G8jQbEo.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/25. Margin of Error-slBW5Neh2cs.zh-CN.vtt
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Part 11-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning-Xcb9jjjAm60.pt-BR.vtt
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Part 21-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-3uUwfgOUT0Y.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-TBJY7UsKtYU.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/01. Introduction to Probability-HeoQccoqfTk.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-BRL0ZuvBm0U.zh-CN.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Tp5WCAJiCRY.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-CML5XbavX0w.ar.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-mPN46IqnT1c.pt-BR.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Background Of Bootstrapping-6Vg5kGoDl7k.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/23. Analyzing Narrative Structures-xgm7DYBijo0.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/32. Reducing Uncertainty-zuFMhmKQ--o.zh-CN.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2 Solution-ncqhpqt0Mik.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/22. Conduct Hypothesis Test-EeI8F1_7zbQ.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-QX_KFUXtHkw.en.vtt
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Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-ieiQqLicBjg.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/06. Wide and Long Format-zlaeISxRESQ.zh-CN.vtt
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Part 11-Module 01-Lesson 01_Welcome to Machine Learning/03. Introduction Pt. III-0ZuxGhiqo5U.zh-CN.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-WjRAjbeG0RE.ar.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-QX_KFUXtHkw.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center-CBaw2pGOO3A.pt-BR.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-XqEQG4qo94I.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/34. Keyboards - SD of Differences--wbCbKqqaZY.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/52. The Purpose of the Grammar of Graphics-pZyrfzuB5FE.zh-CN.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure-z_Gp9ttyiwg.zh-CN.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/06. Example of Sampling Distributions - Part I-1XezzP6kxUE.zh-CN.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/14. Cleaning For Quallity -qyixEwMRtWA.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-pX849ta6kaI.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.es-ES.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/17. Plotting in Pandas-ujJShz9YfAU.en.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-vfEi3aOawTI.pt-BR.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/20. Interactions And Higher Order Terms-AOfXMiJgo48.en.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/18. Plotting in Pandas-ujJShz9YfAU.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null-7AGEhuipHl4.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-Fkm7ogOussQ.zh-CN.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/08. Writing READMEs with Walter-DQEfT2Zq5_o.pt-BR.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/07. Categorical Ordinal Nominal Data-k5bLaPGY2Vw.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.pt-PT.vtt
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Part 11-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video-GJviz-sIq9w.pt-BR.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-Nmf80xB1DN0.zh-CN.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Ilu1JjjAbwA.zh-CN.vtt
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Part 11-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning-Xcb9jjjAm60.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/02. One Number to Describe Data-6QfvhQ0En0E.es.vtt
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Part 13-Module 01-Lesson 04_Design Principles/50. Grammar of Graphics and D3 Functions-rADl_md-WNM.zh-CN.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Introduction To Notation-ISkBSUVH49M.pt-BR.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-omL8MVZjLts.ar.vtt
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Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-5j6VZr8sHo8.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (Before Cleaning)-jJH3H8Rqv8s.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-nqMT8qTmQPY.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-5Uon6hUTl8Y.ar.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/11. Z-1MZnEo0UVX4.zh-CN.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/15. Calculating a Confidence Interval-T-QWVJtXHAs.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/01. Intro to Creating Tables-mIIL-p2gaK4.ar.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-_c_chcNiHyo.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-HSeIrqW-YGw.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.ja.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/09. Pandas Axis Names-8vr8KQuJLcQ.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-ZO7y9tsSQ0A.ja.vtt
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Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.ja.vtt
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Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.th.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/09. Pandas Axis Names-8vr8KQuJLcQ.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-veRRrAR2xF4.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-veRRrAR2xF4.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-4Aj_qdImmGo.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/25. Algorithms for Minimizing Squared Errors-Dw_9Dp6wcJ8.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-97v0kEWjcmg.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/20. Negative Space-3toURbAUt9s.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/22. Conduct Hypothesis Test-EeI8F1_7zbQ.pt-BR.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-49B5hlxzTRc.ar.vtt
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Part 12-Module 01-Lesson 04_Land a Job Offer/01. Land a Job Offer-ZQJoT8QL_hw.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/19. D3 Scales-pFRoUknUJl8.en-US.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/16. Measure Variability-j5fGEYLUOD4.pt-BR.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/02. Parch Posey Database-JOMI560DgXg.en.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-lEl0alktZkM.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-lEl0alktZkM.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Lv22Usic4A8.zh-CN.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-QCakJ5gxF5w.pt-BR.vtt
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Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-HSeIrqW-YGw.ja.vtt
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Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-cwjvMYPB1Fk.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.ja.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.ar.vtt
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Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-3r8OR2yQ-KI.pt-BR.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/06. Checking Invariants, Part 2-Mftti4FSjn4.en.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.pt-BR.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision-pZu3Gr5cAUU.pt-BR.vtt
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Part 12-Module 01-Lesson 04_Land a Job Offer/01. Land a Job Offer-ZQJoT8QL_hw.es-MX.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/19. D3 Scales-pFRoUknUJl8.en.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/01. Instructors Introduction-lIvm8urf4GE.ar.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-uSXJtEpwEVM.es.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score-1V7JzqCfe9o.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-hS7cpq-sOeQ.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.zh-CN.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/04. More Examples-gj-or8b8TmM.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-4Ywln5AT6Hc.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.it.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/10. 95 CI with Exact Z-Scores-Ipj62kdE3Lo.pt-BR.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/22. Outro -lfWT0kLfe8c.en.vtt
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Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-cwjvMYPB1Fk.pt-BR.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-mPN46IqnT1c.en.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-kutWDS1chik.pt-BR.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/09. Querying Using Field Selection-V2UMNT9VBrw.zh-CN.vtt
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Part 12-Module 02-Lesson 06_Graphs/01. Graph Introduction-DFR8F2Q9lgo.en-US.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/32. Enter Update Exit-lmDLMOPOj5I.pt-BR.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/10. AVG-diqCDztOL64.zh-CN.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/16. GROUP BY Part II-0HQ-TshNNQA.zh-CN.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations--InZYjwPsKs.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-GGCzMmOpQqQ.ar.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/07. Intro To Stanley Terrain Classification-TwFhCeov85E.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/24. Minimizing Sum of Squared Errors-E1XzT619Eug.ar.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations--InZYjwPsKs.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/10. Two-Tailed Critical Values 0.05-VCdJJTk2Izk.pt-BR.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-FdRVdkASudw.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.es-NI.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-Keh5GwaSWdk.zh-CN.vtt
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Part 12-Module 02-Lesson 06_Graphs/01. Graph Introduction-DFR8F2Q9lgo.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-kTsQyHV_T5E.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-Vp43h6ZRyoQ.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables-e8zSXnyskro.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-gg7SAMMl4kM.en.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-Vp43h6ZRyoQ.pt-BR.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/08. The Experiment Page--GlHaeB-vic.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-UNqgFhKvCL4.zh-CN.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/10. Integrity and Mindset-zCOr3O50gQM.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.es.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds-Bs-wLbPOAfs.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/07. Javascript Debugger-AzbaV5CT9es.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/44. Adding Events to Buttons-UXRemP4hIyw.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/13. Match Boxplots-imNv6Q8GiQM.en.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/33. Adding Bars and Text-EcwO8YPrn-M.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/28. Changing the Chart Type-wsjvZQaKIgA.ar.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/18. UNC-Ko-g24l1LpQ.es.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/39. Keyboards - CI for Dependent Samples-83VGOXwmjUw.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 2-9YPOlROXNZM.zh-CN.vtt
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/16. 34. Landmines-8ScnVyC24s8.pt-BR.vtt
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Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.ja.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.pt-BR.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/02. NULLs-WYUkLKn6XCw.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size-rS6udGwrN90.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-3uUwfgOUT0Y.en.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-Uf_KdjVT2Xg.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-LwazT9KH76w.en.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-Uf_KdjVT2Xg.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-8IzQG_2WAcs.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/38. World Cup Participation Animation-2GN_nwKc_ZA.ar.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/10. Theoretical Normal Distribution-vyy5yUt1IrE.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above-CoFbRt4icdQ.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/26. Rent - Cohen's d-admfaazbCnY.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/08. Aggregations-TE9uvPwvpu4.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-ZO7y9tsSQ0A.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/08. Data Visualization and You-m_nSthII_IE.pt-BR.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-E55ujT-kf5E.ar.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Subqueries Using WITH-IszTmDKyKHI.zh-CN.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI-diHsJPQHtKc.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-6BBUSWrSuFA.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/19. Randomness-KwmQDhUkLAE.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/19. Randomness-KwmQDhUkLAE.es.vtt
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Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/30. Rent - Increase n-UUn6ETq08SU.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.ja.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/01. Finding Stories-vVWFVaiWomw.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/05. Does Range Change-sCHCU42thsI.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250-mPcWDYTRDs8.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/09. Pandas Axis Names-8vr8KQuJLcQ.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.ar.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-TBJY7UsKtYU.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/05. Visualizations in Data Science-UCKGGQ4LFjo.en.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/01. Introduction-AyeKXinJ3W8.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/09. Pandas Axis Names-8vr8KQuJLcQ.en.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.en.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/28. Show Me-Jpk99mgmwaA.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.ar.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/10. ALIAS-viWHJaxWTvw.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.th.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/32. SD Social Networkers-R6KT9-ZbQ4c.zh-CN.vtt
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Part 12-Module 02-Lesson 02_List-Based Collections/08. Stacks-DQoCO8aGcNc.en-US.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-8IzQG_2WAcs.en.vtt
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/02. Data Overview-V-iPdJfrscQ.en.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.ar.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/12. Define Outlier-7rLkGwsbMUY.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings-0-LYyC_70jk.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-TU63rBOwXQ8.en.vtt
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Part 11-Module 01-Lesson 03_SVM/11. SVM Decision Boundary-8hEjeR0qLnA.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-tUeaXXT2oDI.ar.vtt
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Part 11-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video-GJviz-sIq9w.en.vtt
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Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-K4gGK4ScT7M.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-aW9OOZKfqR8.ar.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.pt-BR.vtt
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/10. 27. English Teaching-HmsNljRIsr4.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age-GFKRNBnFGVU.zh-CN.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion-SRXNBlvW-xw.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-Bb2K_pql26Y.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-PXNaLWJ5SKg.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/06. CREATE and DROP databases-3kycKkbQK6A.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-5zoL8YdM6sI.ja.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.ja.vtt
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Part 12-Module 02-Lesson 02_List-Based Collections/08. Stacks-DQoCO8aGcNc.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/02. One Number to Describe Data-6QfvhQ0En0E.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/06. CREATE and DROP databases-3kycKkbQK6A.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-mIzPoh_kqw4.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/10. Two-Tailed Critical Values 0.05-X5GWgtZEsgc.en.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/06. Checking Invariants, Part 2-Mftti4FSjn4.pt-BR.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/06. CREATE and DROP databases-3kycKkbQK6A.zh-CN.vtt
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Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-0QiU3p8POHk.pt-BR.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above-CoFbRt4icdQ.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/23. Wrap-Up-DZa6UOGet_g.ar.vtt
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Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.ja.vtt
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Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-3r8OR2yQ-KI.en.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-FLpXmoHp7eE.en.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/07. How Databases Store Data-H0C9z_sRvLE.zh-CN.vtt
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Percentiles-Qro8uvysnys.en.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-FLpXmoHp7eE.en.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/22. How Databases Store Data-H0C9z_sRvLE.zh-CN.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/08. Writing READMEs with Walter-DQEfT2Zq5_o.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy-m989etSymQQ.ja.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/21. Information Gain-KYieR9y-ue4.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/28. How Visualizations can Save Lives-VUllIatQ3tI.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.es-ES.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-1R44jvxIPJY.ja.vtt
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Part 13-Module 01-Lesson 04_Design Principles/23. Careful with Color-aKwXLGs0Rfs.ar.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-31yCnTUNzts.pt-BR.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/09. Combining Data-7KICenO-lKc.pt-BR.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/09. Continuous Distribution-ytUY1_EfxPk.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-AO8vSyAtfV4.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.en.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.en.vtt
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Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-_TJeoCTDykE.ar.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/15. Why Even Create Graphics-lqI3LFwMVUc.zh-CN.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Why Even Create Graphics - Data Visualization and D3.js-lqI3LFwMVUc.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.ar.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/15. Calculating a Confidence Interval-T-QWVJtXHAs.en.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/15. Two Useful Theorems-jQ5i7CALdRQ.zh-CN.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/22. Popular Chris-cRb2ONJAvog.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.ar.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/22. Find P-Value-pwQ7IQgremk.en-US.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-PXNaLWJ5SKg.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-RfYFqGPxMQM.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/35. What's Next-mKJkmv7h9ro.pt-BR.vtt
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/21. 37. Insomnia-HbnB5SQqmoM.zh-CN.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=-rQivl4aJCOI.zh-CN.vtt
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Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.en.vtt
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Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.es-ES.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-1R44jvxIPJY.zh-CN.vtt
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Part 21-Module 01-Lesson 01_Why Python Programming/03. L1 03 Programming In Python V4-O1cTNYAjeeg.en.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=-rQivl4aJCOI.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-Vp43h6ZRyoQ.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-FY9_6rOPk6c.ar.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-Vp43h6ZRyoQ.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/22. Find P-Value-pwQ7IQgremk.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/02. Visual Encodings Recap-zyroaZ34ltA.ar.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-SxCK2_82FfQ.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.th.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/01. Introduction to Multiple Linear Regression-b26v8HK-8-o.zh-CN.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download II-T4iFJoHb_qU.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-zxeKDuSK31M.es.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/30. Hot Beverage-r-TWqzDJZJs.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/10. Dimple Axes, Series and Fields-nSqsoDChbEU.en.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/06. SUM-0zUP14PeiXk.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.pt-BR.vtt
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Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-ADNFKiAjmWA.en.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/04. Test Cases-7CNatJ7PqZ4.pt-BR.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends-19ZQP5wzmKA.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.it.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-Vx9bxJHQJf8.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-Vx9bxJHQJf8.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.es-ES.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.es-MX.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-AnksTk1zI3Y.ar.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.es-ES.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/29. One Dimension-vsqelq1aYy8.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores-2OKqKX7DnMQ.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.sv.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-vfEi3aOawTI.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.ja.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/25. You Can Iterate-QsJqoJYhTiw.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete--uRSI_oybJQ.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts-i6nppkOcNoE.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/18. UNC-Ko-g24l1LpQ.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/40. Jelly Beans-1HmiArFN-EI.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/65. Lesson 3 Recap-MmJ6fBojjiA.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.es-MX.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.en.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/01. Introduction to Maps-JEw3iQAnGKQ.en-US.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.th.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/05. DF - Add to 10-mb1eR8nb9t4.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-5zoL8YdM6sI.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.ar.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/31. Raining-R5Jgz8SaVqM.en.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/01. Introduction to Maps-JEw3iQAnGKQ.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/34. Spreadsheet SD-gqXiI9v7h8A.pt-BR.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-QCakJ5gxF5w.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-6BBUSWrSuFA.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-KFVdS328iC8.en.vtt
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Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ujpjeaxE6GU.ar.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/10. Interview Wrap-Up-sz4Ekcu9a_Q.zh-CN.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/31. Lesson Conclusion-quP9Njc2aMg.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-BHFxJmzw1gY.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.es-MX.vtt
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Percentiles-Qro8uvysnys.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center-CBaw2pGOO3A.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/38. Bessel's Correction-bHVPpomkUYs.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-BngCW1fjvFk.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-_c_chcNiHyo.zh-CN.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/25. NEW Create a Radius Scale-fdylxSVOsnw.en-US.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-kutWDS1chik.en.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/04. What is Data-ldTDAjrVsA8.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-FLpXmoHp7eE.pt-BR.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/02. Parch Posey Database-JOMI560DgXg.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.th.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-FLpXmoHp7eE.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.zh-CN.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/04. Total Number of Samples-q5JgPXsHSrA.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-cwjvMYPB1Fk.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-dkLEMSLTxvk.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-uSXJtEpwEVM.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1-bFDJ_FstSZ4.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots--gIxCjLXCEs.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.ar.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/25. NEW Create a Radius Scale-fdylxSVOsnw.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/44. Adding Events to Buttons-UXRemP4hIyw.pt-BR.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/03. Entity Relationship Diagrams-YY2TAJLEINA.pt-BR.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.ja.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/13. Match Boxplots-xg4WOp3v-CM.pt-BR.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5-ONwh_Dcd6j8.zh-CN.vtt
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Introduction to Window Functions-u3qLjP8KMKc.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.en-GB.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.ja.vtt
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Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.ar.vtt
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Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-7LGaeYfvRug.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-aseCJf5mrdo.ar.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/01. Introduction to Advanced SQL-i0VaVPIKUks.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.en.vtt
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/10. 27. English Teaching-HmsNljRIsr4.es.vtt
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Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-ICUYxC-8d7o.ja.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/03. Projects and Progress-Z9ZLMQWsbsk.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/26. Sum of Squares-fktfjG1SnkI.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/16. Indulge Curiosity-9HnRVGjqNqE.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots-AtmfksGs-0I.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.en.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/01. 26 Spread Part 1-zb76Z_viYLY.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/37. Regression Mini-Project Video-CrD9jN3rBM8.zh-CN.vtt
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Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.en.vtt
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Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.ar.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/09. Model Diagnostics-XsYFAtzF6e4.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean-DM1zSW5aoCc.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/23. Rent - t-Critical Values-0tcbCIrJGlM.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics-meNSO42JF6I.pt-BR.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate -CDRmFJHywp8.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.ja.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next-AwpX6HkhL0k.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio-XtDLvgt7LQk.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value-tef9eqI2SVY.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-QX_KFUXtHkw.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-bgT8sWuV2lc.ar.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-QX_KFUXtHkw.zh-CN.vtt
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Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.ja.vtt
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Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.ar.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/28. Variability Summary-sDejdrYe8cg.zh-CN.vtt
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Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-N6hiygoT9FE.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-32WHsQi1UWc.en.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/20. Precision and Recall-3vT0kSBCLdU.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/21. Shape of Distribution When n Increases-kJ4Y8a1rOkY.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/21. Conclusion-JUI9VHvwI08.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/12. Data-d7aERRVkccY.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/12. Data-d7aERRVkccY.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.zh-CN.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2 Solution-ncqhpqt0Mik.zh-CN.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/31. Final Thoughts On Shifting To Machine Learning-YkZFjZ3Fx8A.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-31yCnTUNzts.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.es.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.en.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/13. Feature Scaling Mini-Project Video-e6zbTFctnJU.ar.vtt
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Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-ADNFKiAjmWA.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/11. In-Place vs. Not In-Place-TVyv8acRPrs.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/01. Introduction-wwzSxJvGwf0.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/23. Analyzing Narrative Structures-xgm7DYBijo0.zh-CN.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.en.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place-TVyv8acRPrs.zh-CN.vtt
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/04. 02 Joining Tables-vSjKBMgW1Fw.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-fpPPozvkpWM.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.pt-BR.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/08. The Experiment Page--GlHaeB-vic.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.it.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/20. Precision and Recall-3vT0kSBCLdU.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download II-T4iFJoHb_qU.pt-BR.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 -Ngl_TsqhMsc.zh-CN.vtt
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Part 21-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.zh-CN.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Visual-PVbOzw5libM.pt-BR.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/09. Combining Data-7KICenO-lKc.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/11. Generalize Point Estimate-i4lFgFq8Kpo.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.ko.vtt
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Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.zh-CN.vtt
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Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-7LGaeYfvRug.pt-BR.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/10. ALIAS-viWHJaxWTvw.pt-BR.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.hr.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-S4KbzIyEwV8.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/33. Probability of Obtaining Mean--boAkUs-amM.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/15. Standardizing Each Column Again-7NofF-s1UGY.ar.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/18. Adding the Y-axis-22JU1uui9y4.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/18. Adding the Y-axis-22JU1uui9y4.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/12. DataFrame apply()-aGEUhSRys8w.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy-m989etSymQQ.en.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.es-ES.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/12. DataFrame apply()-aGEUhSRys8w.pt-BR.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-kT0jBsXOouw.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-0X7voyhbZ8k.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/06. Estimating Your Audience Size-FfzVPWM5DZ8.en.vtt
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/15. Sets and groups with Trina-I59eqlvfMZk.zh-CN.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/32. Hypothesis Testing Conclusion-nQFchD4XPPs.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NkyYCLoJVyE.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/31. Raining-R5Jgz8SaVqM.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/32. Keyboards-bLDBg86nm6o.zh-CN.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-Bb2K_pql26Y.zh-CN.vtt
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/16. 34. Landmines-8ScnVyC24s8.es.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-N5T8ouw1SGc.pt-BR.vtt
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Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-pxaXkCjukGM.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.es-ES.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/34. Spreadsheet SD-gqXiI9v7h8A.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-sbQXPn9xLvI.zh-CN.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-lEl0alktZkM.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-lEl0alktZkM.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.zh-CN.vtt
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Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-zTI5Ci5WWzM.ar.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.zh-CN.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Introduction To Notation-ISkBSUVH49M.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. 141 Assess Intro V4-mdrAdtziXh4.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/21. Conclusion-JUI9VHvwI08.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/32. Enter Update Exit-lmDLMOPOj5I.en.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/06. SUM-0zUP14PeiXk.en.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/21. Conclusion-JUI9VHvwI08.en.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/01. Introduction-2Y279421n3A.ar.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.ja.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/02. USCF Distribution-GNAZ2S3igr4.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/18. Debugging Data Analysis Code -ReoDup994zk.en.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/17. Why Data Dashboards-8ni2lCqAVvQ.en.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution-oERHYF9QCkY.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/35. What's Next-mKJkmv7h9ro.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-pq31lSXEQl0.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-rGw4xFsUUqE.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.ja.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/09. How Does Project Submission Work-jCJa_VP6qgg.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-mIzPoh_kqw4.es.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/16. Indulge Curiosity-9HnRVGjqNqE.en.vtt
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Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-0QiU3p8POHk.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/14. Adding a Series with Dimple-clyCsNwceP0.pt-BR.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Why Are Sampling Distributions Important-aDFDOCJKoH0.pt-BR.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/14. Cleaning For Quallity -qyixEwMRtWA.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-Vp43h6ZRyoQ.zh-CN.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/13. Data Modeling in JSON--rnzkOofIv0.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-Vp43h6ZRyoQ.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/19. Null Hypothesis-Klv_8052hoA.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/12. Affect t-Statistic-HMfd6rQrI0Y.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-ygveMIhCtDg.ja.vtt
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Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.ja.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet II-M0qR7to1fl4.pt-BR.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/27. Conclusion-IanoSiET2nA.zh-CN.vtt
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Part 21-Module 01-Lesson 01_Why Python Programming/03. L1 03 Programming In Python V4-O1cTNYAjeeg.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/03. Degrees of Freedom-nJlJ0vlTRUs.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.pt-BR.vtt
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Part 12-Module 02-Lesson 06_Graphs/01. Graph Introduction-DFR8F2Q9lgo.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-CML5XbavX0w.pt-BR.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.es-ES.vtt
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Part 11-Module 01-Lesson 07_Regressions/21. Linear Regression Errors-A4nPMEOcUd4.zh-CN.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/01. Introduction to Maps-JEw3iQAnGKQ.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/30. Color Blind-mmw24xSEB3A.pt-BR.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.ar.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/09. HTML File Structure -4ef_Dr_SXTw.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/12. Example Details-aR6Z7ggnjEY.pt-BR.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-RfYFqGPxMQM.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-pq31lSXEQl0.pt-BR.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/03. What is the Difference-I3tQvrCgNrQ.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.ar.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Why Are Sampling Distributions Important-aDFDOCJKoH0.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-xU84TShi7I4.en.vtt
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Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-3r8OR2yQ-KI.zh-CN.vtt
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Part 12-Module 01-Lesson 04_Land a Job Offer/01. Land a Job Offer-ZQJoT8QL_hw.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-m8d9J5w3axY.en.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/22. Outro -lfWT0kLfe8c.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.ar.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/18. Comparing Two Samples-kaVG7U0rda8.en.vtt
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Part 17-Module 01-Lesson 14_Regression/21. Recap-DzMi27LI5l4.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/21. Be Happy and Get Rid of Negatives-_ULZYGI6LPQ.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value-tef9eqI2SVY.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score-1xXceRXrsg8.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/22. SEM-gl4ogBY9AOI.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/02. What to Do First-TgAIx_NFaD8.zh-CN.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-kTsQyHV_T5E.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-LwazT9KH76w.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.th.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (Before Cleaning)-jJH3H8Rqv8s.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/09. HTML File Structure -4ef_Dr_SXTw.en.vtt
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Part 21-Module 01-Lesson 03_Control Flow/02. Indentation-G8qUNOTHtrM.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/03. Meal Prices-gzu9UcNF0_k.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots-AtmfksGs-0I.ja.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-ZO7y9tsSQ0A.zh-CN.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-Mt5TWGYacJs.ja.vtt
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Part 13-Module 01-Lesson 04_Design Principles/01. Lesson Overview-k5T30IHD8T8.pt-BR.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion-xYqxZQmXCdI.ar.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-6BBUSWrSuFA.ja.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.zh-Hans.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.pt-BR.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/20. SD of Standardized Distribution-LuI1poHmFOw.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/26. Rent - Cohen's d-admfaazbCnY.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/52. D3 Hides Complexity-iNXkYbkD3IU.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/03. Degrees of Freedom-nJlJ0vlTRUs.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/34. Keyboards - SD of Differences--wbCbKqqaZY.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/06. r^2-X5F1reyQ_5U.zh-CN.vtt
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Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.en-US.vtt
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Part 13-Module 01-Lesson 04_Design Principles/01. Lesson Overview-k5T30IHD8T8.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/30. Color Blind-mmw24xSEB3A.en.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.ja.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.it.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.en.vtt
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Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3--XfG5hXveiE.zh-CN.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.en.vtt
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Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.th.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-HVa4G8jQbEo.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-HVa4G8jQbEo.es.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/10. Two-Tailed Critical Values 0.05-VCdJJTk2Izk.en.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/02. NULLs-WYUkLKn6XCw.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds-Bs-wLbPOAfs.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-buxApBhZCO0.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/01. Welcome to Evaluation Metrics Lesson-IHuFWRM9f9Q.zh-CN.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-32WHsQi1UWc.pt-BR.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.ja.vtt
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Part 21-Module 01-Lesson 02_Data Types and Operators/35. L2 01 Compound Data Structures V1-jmQ8IKvQgBU.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/12. DataFrame apply()-aGEUhSRys8w.en.vtt
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Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/12. DataFrame apply()-aGEUhSRys8w.en.vtt
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/16. 34. Landmines-8ScnVyC24s8.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-zxeKDuSK31M.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/38. Bessel's Correction-bHVPpomkUYs.en.vtt
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Part 17-Module 01-Lesson 13_Case Study AB tests/09. Experiment II-fq4eO7CybA4.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/37. Probability of Mean-RNgSdHPE4aA.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/65. Lesson 3 Recap-MmJ6fBojjiA.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/17. Plotting in Pandas-ujJShz9YfAU.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-TU63rBOwXQ8.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-xU84TShi7I4.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-KFVdS328iC8.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.ja.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. 141 Assess Intro V4-mdrAdtziXh4.en.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/18. Plotting in Pandas-ujJShz9YfAU.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-kTsQyHV_T5E.es.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds-WeS0ogG86nk.en.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-yLeLxDyXCSY.ar.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-hW_1ASU-j8A.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.ja.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/16. Measure Variability-j5fGEYLUOD4.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value-6Z3BJWRuOAE.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.ar.vtt
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Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-N6hiygoT9FE.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-m8d9J5w3axY.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/18. Roll 5 Dice-BgBEqvjLNig.en.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.pt-BR.vtt
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Part 12-Module 02-Lesson 02_List-Based Collections/08. Stacks-DQoCO8aGcNc.zh-CN.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-mPN46IqnT1c.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.ar.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/16. How Do We Choose Between Hypotheses-JkXTwS-5Daw.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/18. UNC-Ko-g24l1LpQ.en.vtt
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Part 11-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.pt-BR.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/11. Enron Dataset Mini-Project Video-0zGp5er3fy4.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/14. Adding a Series with Dimple-clyCsNwceP0.en-US.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-uSXJtEpwEVM.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-tjEua8efugg.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/25. NEW Create a Radius Scale-fdylxSVOsnw.zh-CN.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/03. What Is Coming Up-oDJsnQcCPr4.pt-BR.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/12. What Can You Create In Tableau-gNqIvf5iJA8.ar.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/32. Location of Mean on Distribution-_kADa-a_UD8.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/14. Adding a Series with Dimple-clyCsNwceP0.en.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.ar.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-nu2OKJwDvvE.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.es-ES.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.ar.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -BS_p9kwMEMk.en.vtt
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Part 21-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/37. Visualize Every Game of the World Cup-fxgnL-Lv684.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-0plipvHyAlk.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-0plipvHyAlk.pt-BR.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess-mCZxHNB1u4w.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/09. Pandas Axis Names-8vr8KQuJLcQ.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots--gIxCjLXCEs.ja.vtt
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Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-ICUYxC-8d7o.zh-CN.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion-SRXNBlvW-xw.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/09. Pandas Axis Names-8vr8KQuJLcQ.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/19. Randomness-KwmQDhUkLAE.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/19. Randomness-KwmQDhUkLAE.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null-7AGEhuipHl4.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/24. Final Thoughts-CNGDocH1k3k.ja.vtt
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Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.en-US.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/52. D3 Hides Complexity-iNXkYbkD3IU.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.ja.vtt
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Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/41. The World Cup Narrative-nnqZR2GdcAA.zh-CN.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.ar.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/32. Hypothesis Testing Conclusion-nQFchD4XPPs.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.ar.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/20. Course Conclusion-6aBIwp3n7_8.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision-pZu3Gr5cAUU.en.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.ja.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/32. Location of Mean on Distribution-_kADa-a_UD8.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.en.vtt
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Part 12-Module 01-Lesson 03_Interview Fails/01. Interview Fails-FD6UNqMa0xc.pt-BR.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/06. Runtime Analysis-8bI9OgOB2qI.en-US.vtt
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Part 17-Module 01-Lesson 13_Case Study AB tests/16. Drawing Conclusions-s-4ghG9vrGQ.zh-CN.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/13. Line Plots-GsaBT47pjgQ.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/16. Roll 2 Dice-OVeEr0CSe8U.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/39. Keyboards - CI for Dependent Samples-83VGOXwmjUw.en.vtt
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Part 11-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.en.vtt
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Part 17-Module 01-Lesson 04_Probability/01. Introduction to Probability-HeoQccoqfTk.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-hW_1ASU-j8A.ja.vtt
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Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-udJvijJvs1M.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-QBaNltqVj_0.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/16. Establishing Statistical Significance-C22VZ_mY5RM.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-ICUYxC-8d7o.pt-BR.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/06. Runtime Analysis-8bI9OgOB2qI.en.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-ClkOE3kdvLs.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.ar.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.zh-CN.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/12. Using the Z-Table-GF0qAvNKpOA.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-sy_jiSEy-Nw.en.vtt
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Part 12-Module 02-Lesson 06_Graphs/09. Graph Traversal-Dkt-XxHZaZE.en-US.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/19. D3 Scales-pFRoUknUJl8.zh-CN.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.zh-CN.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.ar.vtt
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/10. 27. English Teaching-HmsNljRIsr4.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.ja.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/25. Welcome to the End of Evaluation Lesson-sgFfl-j_oCs.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Visual-PVbOzw5libM.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-Vx9bxJHQJf8.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-Vx9bxJHQJf8.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/13. Match Boxplots-imNv6Q8GiQM.zh-CN.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/12. Example Details-aR6Z7ggnjEY.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings-0-LYyC_70jk.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/37. Visualize Every Game of the World Cup-fxgnL-Lv684.pt-BR.vtt
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview-2X8GJyZUlDo.ar.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/09. MIN MAX-1ewVsgWUih8.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI-llyWJTM8V5o.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-JKZF4qHztv0.ko.vtt
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Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-gg7SAMMl4kM.zh-CN.vtt
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Part 12-Module 01-Lesson 03_Interview Fails/01. Interview Fails-FD6UNqMa0xc.en.vtt
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Part 12-Module 02-Lesson 06_Graphs/09. Graph Traversal-Dkt-XxHZaZE.en.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.hr.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/09. Combining Data-7KICenO-lKc.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median--XPrm7KcCdc.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma-NMnlSnu8DPI.en.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/01. SQL is for Elephants-BYAyquwZmdM.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-3nZ2FL7C3sU.pt-BR.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/03. Entity Relationship Diagrams-YY2TAJLEINA.en.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-veRRrAR2xF4.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-veRRrAR2xF4.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/01. Animation and Interaction-4aBXHspd7WI.pt-BR.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.ar.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/09. How Does Project Submission Work-jCJa_VP6qgg.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-gUXB5GofFKM.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/29. One Dimension-vsqelq1aYy8.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.ar.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.pt-BR.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/03. Projects and Progress-Z9ZLMQWsbsk.zh-CN.vtt
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Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-K-rQ8KnmmH8.pt-BR.vtt
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Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-lS5DfbsWH34.ar.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/15. Problem with IQR-h5l2EP3DR-4.pt-BR.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-JZx1Pyzuo_s.pt-BR.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/09. HTML File Structure -4ef_Dr_SXTw.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/25. Changing Bin Size-fI_SYnWB1XA.es.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-mIzPoh_kqw4.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05-oCQnqFE4uxQ.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-c1gvsNx_ypg.ar.vtt
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/02. Download Tableau Public-2bXsg6SKHG8.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.ja.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.en.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/02. Download Tableau Public-2bXsg6SKHG8.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=-J9FWaCBXhIk.en.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -BS_p9kwMEMk.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=-J9FWaCBXhIk.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center-bsybN1HIH4s.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score-1xXceRXrsg8.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/33. What Happened-LOwWWIXvnhU.zh-CN.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/01. Effect Size-z98xODInLCQ.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error-FpeMuGuo74k.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/19. Null Hypothesis-Klv_8052hoA.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-Hv58aHpWvEE.en.vtt
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Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-ICUYxC-8d7o.en.vtt
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/17. Conclusion-D_ioSXAre1A.pt-BR.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet II-M0qR7to1fl4.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/25. You Can Iterate-QsJqoJYhTiw.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/02. One Number to Describe Data-6QfvhQ0En0E.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.en.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/01. Lesson Introduction-nQBbywNKTVc.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-TBJY7UsKtYU.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.en.vtt
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Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-r5qca6q4Fn4.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/05. Visualizations in Data Science-UCKGGQ4LFjo.zh-CN.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/14. Other Sampling Distributions-Bxl0DonzX8c.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download II-T4iFJoHb_qU.zh-CN.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/22. SEM-gl4ogBY9AOI.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-n7v-y8UrVJ0.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/06. Estimating Your Audience Size-FfzVPWM5DZ8.ja.vtt
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Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.th.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-Hv58aHpWvEE.pt-BR.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/13. Data Modeling in JSON--rnzkOofIv0.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-31yCnTUNzts.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts-q-EjlMl1Bj4.zh-CN.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/18. UNC-Ko-g24l1LpQ.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-WxAWorS2SLg.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-JsFlZfNpVl4.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/14. Adding a Series with Dimple-clyCsNwceP0.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/33. Advantages with CSS-lCTey7ryZ1A.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.en.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-N5T8ouw1SGc.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-ygveMIhCtDg.en.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/25. Welcome to the End of Evaluation Lesson-sgFfl-j_oCs.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.en.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download Solution-SDqdLhgsBNc.ar.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/09. How Does Project Submission Work-jCJa_VP6qgg.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/25. Changing Bin Size-fI_SYnWB1XA.en.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs-Zw3X9BQQKB0.zh-CN.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations--InZYjwPsKs.zh-CN.vtt
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Part 05-Module 01-Lesson 05_Data Quality/06. Difficulty of Quality Metrics-uqCSn9Q9ARk.en.vtt
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Part 12-Module 02-Lesson 06_Graphs/01. Graph Introduction-DFR8F2Q9lgo.pt-BR.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations--InZYjwPsKs.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/07. Chop Off the Tails-NmlhFjNHmXc.ar.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.ja.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.ar.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/03. Choose Your Own Adventure-Ka9nwD0QzTI.zh-CN.vtt
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Part 11-Module 01-Lesson 09_Clustering/17. Clustering Mini-Project Video-68EGMItJiNM.en.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet II-M0qR7to1fl4.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/02. Probability-oR8H9vdtreE.zh-CN.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes-icmKCnOXQdI.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-0OkHWvkwCus.en.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.en.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/10. Theoretical Normal Distribution-vyy5yUt1IrE.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/10. Dimple Axes, Series and Fields-nSqsoDChbEU.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.ar.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/09. The Data Science Process-Kxp2TNV3n5k.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-Uf_KdjVT2Xg.zh-CN.vtt
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Part 12-Module 02-Lesson 06_Graphs/09. Graph Traversal-Dkt-XxHZaZE.pt-BR.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-Uf_KdjVT2Xg.zh-CN.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/01. Effect Size-z98xODInLCQ.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.pt-BR.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/16. How Do We Choose Between Hypotheses-JkXTwS-5Daw.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.en-US.vtt
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Part 12-Module 02-Lesson 05_Trees/10. Binary Search Trees-7-ZQrugO-Yc.en-US.vtt
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/09. Extra Practice With Dashboards-Va2zNfnUC6o.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-HVa4G8jQbEo.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-HVa4G8jQbEo.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results-l_HFnHve3Ok.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.zh-CN.vtt
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Part 11-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project-JEK7-ocWu0M.ar.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean--IGW7WH6CIA.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/19. Finches - Decision-9N6i3RZun5A.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy-m989etSymQQ.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.es.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs-KAOIExZuV_M.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.ja.vtt
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Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.ar.vtt
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Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-xJtmPbEfpFo.en.vtt
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Part 12-Module 02-Lesson 05_Trees/10. Binary Search Trees-7-ZQrugO-Yc.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-K-rQ8KnmmH8.en.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-QBaNltqVj_0.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.es.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median--XPrm7KcCdc.es.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center-CBaw2pGOO3A.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/30. Hot Beverage-r-TWqzDJZJs.zh-CN.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/11. Enron Dataset Mini-Project Video-0zGp5er3fy4.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.en.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-1lNAvDubBfI.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-CML5XbavX0w.en.vtt
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Part 12-Module 02-Lesson 04_Maps and Hashing/01. Introduction to Maps-JEw3iQAnGKQ.zh-CN.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/02. Technical Interlude-QWA06Ro4ix0.zh-CN.vtt
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Introduction to Percentiles-t7SX2ZEdxKA.ar.vtt
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Part 21-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.ar.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NkyYCLoJVyE.es.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.en.vtt
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Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-sy_jiSEy-Nw.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-veRRrAR2xF4.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-veRRrAR2xF4.es.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR-sl51Cpwy5RA.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size-rS6udGwrN90.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro-rR68JXwKBxE.en.vtt
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Part 12-Module 01-Lesson 03_Interview Fails/01. Interview Fails-FD6UNqMa0xc.es-MX.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/59. New Data Stories in the Graphic-9yKFn_R2c_U.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-6LgGDqQLpyc.pt-BR.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning-XDfqzA6nkqk.en.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next-AwpX6HkhL0k.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/20. Equation for Average Deviation-dYbYjtCzQPo.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.pt-BR.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-49B5hlxzTRc.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-xU84TShi7I4.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-P46v39eNSqM.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-Och80L_uNjU.ar.vtt
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Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-aveIz1JYeAg.pt-BR.vtt
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Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-Fi3uuGj8bhs.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.es.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/07. Sampling Distribution-7tlVeUW2t7Q.pt-BR.vtt
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Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-5j6VZr8sHo8.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/01. Animation and Interaction-4aBXHspd7WI.en.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/06. Checking Invariants, Part 2-Mftti4FSjn4.zh-CN.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/20. Interactions And Higher Order Terms-AOfXMiJgo48.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations--InZYjwPsKs.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/24. Overfitting-plx_F2BkwNQ.en.vtt
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Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-z2R5CqjXrkA.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.pt-BR.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Visual-PVbOzw5libM.en.vtt
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Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-W74CdB_pl5M.ar.vtt
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Part 12-Module 02-Lesson 06_Graphs/09. Graph Traversal-Dkt-XxHZaZE.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=-J9FWaCBXhIk.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-6LgGDqQLpyc.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean-DM1zSW5aoCc.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/14. Increase t-tBk_gBWan8k.en.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-cUlEryXX9BM.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.ar.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular-W5qXCZ-nrHM.zh-CN.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values--xVYQQHNNuM.en.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values--xVYQQHNNuM.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.zh-Hans.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-3uUwfgOUT0Y.zh-CN.vtt
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Part 05-Module 01-Lesson 05_Data Quality/01. Introduction-JA7oIPaf9PM.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.ja.vtt
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Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.ar.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-WjRAjbeG0RE.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/32. Keyboards-0m5k7Ni1O48.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-uHIZl6MCiPY.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.en.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-xYxD4GD1woo.ar.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/01. Instructors Introduction-lIvm8urf4GE.en.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/20. You Can Iterate-ZU8EnPbR-pk.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-n1EbdV_CTcc.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-3nZ2FL7C3sU.en-US.vtt
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Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-3nZ2FL7C3sU.en.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.ar.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/15. Problem with IQR-h5l2EP3DR-4.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.ja.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/01. Lesson Introduction-nQBbywNKTVc.en.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.zh-CN.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-mpYpT6nZVEo.ar.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download-a5o3ck1bxEs.ar.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/10. Calculate SDs-x-VMDl-3p7M.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-AO8vSyAtfV4.zh-CN.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/10. Intro to Screen Scraping-RJyVIgUUemE.ar.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.pt-BR.vtt
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Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-7LGaeYfvRug.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.zh-CN.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-kutWDS1chik.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NkyYCLoJVyE.en.vtt
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Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-xJtmPbEfpFo.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/13. Manipulating DOM Nodes-RMUHrUa7HR0.en-US.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/37. Visualize Every Game of the World Cup-fxgnL-Lv684.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.th.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.zh-CN.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above-CoFbRt4icdQ.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-783QmxtIx58.ar.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/17. Why Data Dashboards-8ni2lCqAVvQ.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-uHIZl6MCiPY.en.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/13. Manipulating DOM Nodes-RMUHrUa7HR0.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/27. Making Decisions about Uncertain Data-GM8MV0FvCUo.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.th.vtt
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Part 21-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/15. Getting Data from First Week -adqc5fF5B8Y.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables-08GsrEIOP9Q.ar.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.pt-BR.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-nu2OKJwDvvE.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-PRjmvj6Vubs.ar.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05-oCQnqFE4uxQ.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.pt-BR.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/03. Confirming Inputs-8lPTOG1yLsg.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/35. What's Next-mKJkmv7h9ro.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.ja.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/24. Final Thoughts-CNGDocH1k3k.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.pt-BR.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.en.vtt
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Part 11-Module 01-Lesson 03_SVM/24. Overfitting-plx_F2BkwNQ.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.ar.vtt
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Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.ar.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/14. Confidence Intervals-fDkfHKODOcQ.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.en.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/02. NULLs-WYUkLKn6XCw.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.th.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/05. Does Range Change-sCHCU42thsI.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/32. Location of Mean on Distribution-_kADa-a_UD8.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-0OkHWvkwCus.pt-BR.vtt
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Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-0QiU3p8POHk.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.zh-CN.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess-mCZxHNB1u4w.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/22. Find P-Value-pwQ7IQgremk.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/26. Evaluation Mini-Project Video-s13K9G1VaWM.en.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-ClkOE3kdvLs.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-S4KbzIyEwV8.en.vtt
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Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-5zoL8YdM6sI.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.zh-CN.vtt
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Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-ADNFKiAjmWA.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/18. Adding the Y-axis-22JU1uui9y4.zh-CN.vtt
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/01. Lesson Overview-DkjRzNwjSfo.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/17. Find Standard Error-YNuoRW6EyEo.zh-CN.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/10. Interview Wrap-Up-sz4Ekcu9a_Q.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/21. Conclusion-JUI9VHvwI08.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-KFVdS328iC8.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-n1EbdV_CTcc.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/23. Careful with Color-aKwXLGs0Rfs.en.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.it.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/21. Conclusion-JUI9VHvwI08.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.pt-BR.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/19. Congratulations!-_FPpbuuW-1o.ar.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject-K2OncV6Bzo8.pt-BR.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-IC47yHGmgMk.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-8QEAYYIyopY.en.vtt
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Aliases for Multiple Window Functions-RWe03bULYnM.ar.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-8QEAYYIyopY.en.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/04. Manual Vs Programmatic Cleaning -AQFBVQy_HyY.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-Xo3Le7VTZZM.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/02. Alpha Levels-VuEwqXDd1Rs.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-si8AcC5pTfM.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.pt-BR.vtt
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/01. Case Study Introduction-r8uEDyBylHY.en-US.vtt
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Part 21-Module 01-Lesson 03_Control Flow/02. Indentation-G8qUNOTHtrM.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-si8AcC5pTfM.pt-BR.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI-diHsJPQHtKc.en.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Tp5WCAJiCRY.zh-CN.vtt
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview-2X8GJyZUlDo.pt-BR.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/20. Precision and Recall-3vT0kSBCLdU.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/30. Standard Deviation-0seYYIPBXxI.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/03. Degrees of Freedom-ZXkeT8mN4lg.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-S4KbzIyEwV8.es.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null-7AGEhuipHl4.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-mIn7nMR092Q.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-FY9_6rOPk6c.pt-BR.vtt
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Part 11-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video-GJviz-sIq9w.zh-CN.vtt
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Part 12-Module 02-Lesson 05_Trees/10. Binary Search Trees-7-ZQrugO-Yc.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-mIn7nMR092Q.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.ar.vtt
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Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-aveIz1JYeAg.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/09. Between 118 and 226-pHNtOrr6bgE.pt-BR.vtt
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Part 05-Module 01-Lesson 05_Data Quality/01. Introduction-JA7oIPaf9PM.en.vtt
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Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.ja.vtt
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Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-ygveMIhCtDg.pt-BR.vtt
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Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-K4gGK4ScT7M.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/30. Standard Deviation-0seYYIPBXxI.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/34. Spreadsheet SD-gqXiI9v7h8A.zh-CN.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/23. Convert to Z-Score-UAHkVUloKbg.en.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/07. Categorical Ordinal Nominal Data-k5bLaPGY2Vw.en.vtt
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Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio-XtDLvgt7LQk.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/02. Visual Encodings Recap-zyroaZ34ltA.pt-BR.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.pt-BR.vtt
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Part 17-Module 01-Lesson 13_Case Study AB tests/09. Experiment II-fq4eO7CybA4.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-6LgGDqQLpyc.es.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median--XPrm7KcCdc.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/10. 95 CI with Exact Z-Scores-Ipj62kdE3Lo.en.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/16. Operators-PlJ_dfdEbR0.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-Z5nOpgKYYj4.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-gUXB5GofFKM.en-US.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/10. Two-Tailed Critical Values 0.05-X5GWgtZEsgc.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/38. World Cup Participation Animation-2GN_nwKc_ZA.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-tjEua8efugg.ko.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-5Uon6hUTl8Y.en.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.ja.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-0OkHWvkwCus.ja.vtt
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Part 11-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro-rR68JXwKBxE.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-aW9OOZKfqR8.en.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/26. Recap-VM6GGNC2q8I.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/09. Sampling Distribution-XUA8rsit0J4.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.ar.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Introduction To Notation-ISkBSUVH49M.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-0plipvHyAlk.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-0plipvHyAlk.es.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-RfYFqGPxMQM.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/01. SQL is for Elephants-BYAyquwZmdM.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-n7v-y8UrVJ0.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-pxaXkCjukGM.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-gUXB5GofFKM.en.vtt
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Part 16-Module 03-Lesson 01_Basic SQL/03. Entity Relationship Diagrams-YY2TAJLEINA.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics-meNSO42JF6I.en.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/25. You Can Iterate-QsJqoJYhTiw.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/13. Match Boxplots-xg4WOp3v-CM.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/09. The Data Science Process-Kxp2TNV3n5k.en.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-FdRVdkASudw.pt-BR.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/25. Conclusion-YS4bR1vQ3Ls.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.zh-CN.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution-QjhQztBNz-Q.en.vtt
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Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-5Uon6hUTl8Y.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/21. Information Gain-KYieR9y-ue4.zh-CN.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-QBaNltqVj_0.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/44. Adding Events to Buttons-UXRemP4hIyw.zh-CN.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/14. Performance Tuning Motivation-aY4_uYWEuoE.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/06. Estimating Your Audience Size-FfzVPWM5DZ8.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots--gIxCjLXCEs.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.es-MX.vtt
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/07. Traveling Salesman Problem-9ruR5Ux63QU.pt-BR.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/19. Exploring Data With Visuals-0i_9t4Wi0Og.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.es-ES.vtt
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Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-aseCJf5mrdo.pt-BR.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.ja.vtt
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Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/34. Determining a Graphic's Effectiveness-BZERcWwQ-PM.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-veRRrAR2xF4.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-veRRrAR2xF4.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/01. Intro to Creating Tables-mIIL-p2gaK4.pt-BR.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/14. Performance Tuning Motivation-aY4_uYWEuoE.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.ja.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-m8d9J5w3axY.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.es-ES.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/11. Multiple Field Queries-tsAh4HonzIw.en.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/26. Evaluation Mini-Project Video-s13K9G1VaWM.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/15. The Benefits of Dimple-PkCeV9KNiMg.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/15. The Benefits of Dimple-PkCeV9KNiMg.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.th.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning-XDfqzA6nkqk.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-aW9OOZKfqR8.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.it.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1 Solution -Noykh9Zt6aI.pt-BR.vtt
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/09. Extra Practice With Dashboards-Va2zNfnUC6o.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-tjEua8efugg.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=-J9FWaCBXhIk.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=-J9FWaCBXhIk.zh-CN.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/04. Total Number of Samples-q5JgPXsHSrA.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.ar.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-PlFG87qPSB4.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/38. World Cup Participation Animation-2GN_nwKc_ZA.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.it.vtt
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Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.es-ES.vtt
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Part 11-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.ja.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.ja.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/06. Runtime Analysis-8bI9OgOB2qI.pt-BR.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/20. Course Conclusion-6aBIwp3n7_8.zh-CN.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.zh-CN.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution-QjhQztBNz-Q.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/06. Zoo-YG8zfeRXAvM.ar.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/24. Final Thoughts-CNGDocH1k3k.en.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!-UjaFiRdHPZg.ar.vtt
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Part 12-Module 02-Lesson 05_Trees/10. Binary Search Trees-7-ZQrugO-Yc.zh-CN.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-J2L_ZU-YMxc.ar.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-vxS-Kh4eI0U.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/52. D3 Hides Complexity-iNXkYbkD3IU.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.en.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/14. Other Sampling Distributions-Bxl0DonzX8c.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-kTsQyHV_T5E.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center-bsybN1HIH4s.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/09. Between 118 and 226-pHNtOrr6bgE.en.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-mIn7nMR092Q.en.vtt
963 Bytes
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-P1NzBPnfl2E.ar.vtt
963 Bytes
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/03. What Is Coming Up-oDJsnQcCPr4.en.vtt
963 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.ar.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate -CDRmFJHywp8.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-mIn7nMR092Q.en.vtt
963 Bytes
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/16. 34. Landmines-8ScnVyC24s8.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score-1xXceRXrsg8.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/31. Raining-R5Jgz8SaVqM.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/27. Rent - CI-QXFudvtcjv0.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-uHIZl6MCiPY.zh-CN.vtt
962 Bytes
Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.pt-BR.vtt
962 Bytes
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-ta5Nz-YCn6g.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.zh-CN.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/16. Confidence Intervals And Hypothesis Tests-T2d9AUnWl-I.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/16. Measure Variability-j5fGEYLUOD4.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-49B5hlxzTRc.en.vtt
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Part 11-Module 01-Lesson 16_Tying It All Together/03. End of Content-MFRkl-aXL8I.pt-BR.vtt
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/07. Traveling Salesman Problem-9ruR5Ux63QU.en-US.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.pt-BR.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/16. Outro-dps7Ti6Lado.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-KEdbHg_utV0.ar.vtt
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Part 17-Module 01-Lesson 14_Regression/21. Recap-DzMi27LI5l4.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/24. Minimizing Sum of Squared Errors-E1XzT619Eug.en.vtt
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/01. Introduction to Data Cleaning-YTtH3NM2BX0.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-0plipvHyAlk.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-0plipvHyAlk.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value-tef9eqI2SVY.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/19. Lessons Completed in First Week -kL0HS6KWRcw.ar.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-1lNAvDubBfI.pt-BR.vtt
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/07. Traveling Salesman Problem-9ruR5Ux63QU.en.vtt
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Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.es-ES.vtt
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Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.hr.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.ja.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.es.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/12. Example Details-aR6Z7ggnjEY.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-N5T8ouw1SGc.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.en.vtt
956 Bytes
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.hr.vtt
956 Bytes
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/12. What Can You Create In Tableau-gNqIvf5iJA8.pt-BR.vtt
956 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.es.vtt
955 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-wBduq7St2Ak.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean--IGW7WH6CIA.en.vtt
955 Bytes
Part 04-Module 02-Lesson 01_Data Analysis Process/18. Debugging Data Analysis Code -ReoDup994zk.zh-CN.vtt
955 Bytes
Part 13-Module 01-Lesson 04_Design Principles/30. Color Blind-mmw24xSEB3A.zh-CN.vtt
955 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-XCf2FDdHDGs.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.pt-BR.vtt
954 Bytes
Part 14-Module 01-Lesson 01_Overview of AB Testing/18. Comparing Two Samples-kaVG7U0rda8.zh-CN.vtt
954 Bytes
Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-ygveMIhCtDg.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.ja.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/27. Making Decisions about Uncertain Data-GM8MV0FvCUo.en.vtt
953 Bytes
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/01. Instructors Introduction-lIvm8urf4GE.pt-BR.vtt
953 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.en.vtt
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Part 21-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.ar.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/15. Problem with IQR-h5l2EP3DR-4.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/16. Indulge Curiosity-9HnRVGjqNqE.zh-CN.vtt
952 Bytes
Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-n7v-y8UrVJ0.zh-CN.vtt
952 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.ja.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/32. Enter Update Exit-lmDLMOPOj5I.zh-CN.vtt
952 Bytes
Part 14-Module 01-Lesson 01_Overview of AB Testing/15. Calculating a Confidence Interval-T-QWVJtXHAs.zh-CN.vtt
952 Bytes
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.ja.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/20. Shoes - 95 CI-Ld7EaNyua4c.pt-BR.vtt
951 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.en.vtt
951 Bytes
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/13. Line Plots-GsaBT47pjgQ.en.vtt
951 Bytes
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/12. DataFrame apply()-aGEUhSRys8w.zh-CN.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/14. Adding a DataFrame to a Series-IaM7ybOda8k.ar.vtt
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Part 05-Module 01-Lesson 05_Data Quality/06. Difficulty of Quality Metrics-uqCSn9Q9ARk.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.ja.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/03. Confirming Inputs-8lPTOG1yLsg.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/12. DataFrame apply()-aGEUhSRys8w.zh-CN.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/14. Adding a DataFrame to a Series-IaM7ybOda8k.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-fpPPozvkpWM.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/01. Introduction to Probability-HeoQccoqfTk.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.ja.vtt
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Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-5dt0N4XN-y4.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.es-ES.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.es-ES.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-_zx9cahSRNE.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/03. Degrees of Freedom-nJlJ0vlTRUs.zh-CN.vtt
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Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.ja.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/19. Randomness-KwmQDhUkLAE.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/19. Randomness-KwmQDhUkLAE.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/02. Alpha Levels-VuEwqXDd1Rs.en.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/01. Introduction to Lesson 5-l2Nab0LY_cI.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-tUeaXXT2oDI.en.vtt
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Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.it.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 -aEGtqoWIJIc.ar.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/10. Two-Tailed Critical Values 0.05-VCdJJTk2Izk.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-OVoEIInUg9A.ar.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/01. Introduction to Advanced SQL-i0VaVPIKUks.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.pt-BR.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.pt-BR.vtt
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Part 21-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.en.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/01. SQL is for Elephants-BYAyquwZmdM.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.en-US.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 2-so5zydnbYEg.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.hr.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-Xo3Le7VTZZM.es.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-tjEua8efugg.zh-Hans.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-omL8MVZjLts.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.ja.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-pq31lSXEQl0.zh-CN.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/01. Introduction to Advanced SQL-i0VaVPIKUks.en.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 3-oVGmi4zBOT8.en.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.en.vtt
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Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.en.vtt
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Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-K4gGK4ScT7M.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/47. Start Creating-Nr1w-Hxjld4.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/38. Bessel's Correction-bHVPpomkUYs.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/03. Degrees of Freedom-ZXkeT8mN4lg.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/01. Lesson Overview-k5T30IHD8T8.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/33. Highlight Countries-wjUenfTcSG0.ar.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/10. Report CI Results 2-eVTzjsolEwI.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.pt-BR.vtt
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/01. Introduction to Data Cleaning-YTtH3NM2BX0.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.en.vtt
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Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.ja.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-Mt5TWGYacJs.zh-CN.vtt
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Introduction to Window Functions-u3qLjP8KMKc.pt-BR.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/07. Categorical Ordinal Nominal Data-k5bLaPGY2Vw.zh-CN.vtt
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Part 17-Module 01-Lesson 14_Regression/01. Regression Introduction-PKqSS0TzXeA.pt-BR.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/04. Manual Vs Programmatic Cleaning -AQFBVQy_HyY.zh-CN.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/13. Data Modeling in JSON--rnzkOofIv0.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.ar.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/33. Advantages with CSS-lCTey7ryZ1A.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/54. Use Variables Wisely-j8o2WUo3-Xg.pt-BR.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/16. Operators-PlJ_dfdEbR0.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.ja.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.pt-BR.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/12. What Can You Create In Tableau-gNqIvf5iJA8.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds-Bs-wLbPOAfs.zh-CN.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-hW_1ASU-j8A.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.zh-CN.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/59. New Data Stories in the Graphic-9yKFn_R2c_U.zh-CN.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-90OMETgfDyk.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-90OMETgfDyk.es.vtt
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Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-rexAHoCGFMs.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-8QEAYYIyopY.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/54. Use Variables Wisely-j8o2WUo3-Xg.en.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/31. Lesson Conclusion-quP9Njc2aMg.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.zh-CN.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-8QEAYYIyopY.pt-BR.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/11. Report Results Effect Size-jjByXJIiCLs.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-Hv58aHpWvEE.zh-CN.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-FdRVdkASudw.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-Ig82ol_4Lgo.pt-BR.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-0X7voyhbZ8k.pt-BR.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/01. Introduction to Lesson 5-l2Nab0LY_cI.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-FY9_6rOPk6c.en.vtt
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Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.pt-BR.vtt
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Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-I_v6ueT0k3M.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-GGCzMmOpQqQ.en.vtt
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Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.ja.vtt
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Part 12-Module 01-Lesson 03_Interview Fails/01. Interview Fails-FD6UNqMa0xc.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/27. The Update Function-z5f-oK0jwZk.ar.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Why Are Sampling Distributions Important-aDFDOCJKoH0.zh-CN.vtt
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Part 09-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/24. Minimizing Sum of Squared Errors-E1XzT619Eug.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values--xVYQQHNNuM.pt-BR.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-4Ywln5AT6Hc.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.hr.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/14. Cleaning For Quallity -qyixEwMRtWA.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values--xVYQQHNNuM.pt-BR.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning-XDfqzA6nkqk.zh-CN.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic-htd-vu8q3po.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width-TYN_LGAV3m8.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.zh-CN.vtt
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Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-aveIz1JYeAg.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/28. Changing the Chart Type-wsjvZQaKIgA.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/13. SD of Sampling Distribution-tPVKll2xFUw.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-Mt5TWGYacJs.en.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/13. Manipulating DOM Nodes-RMUHrUa7HR0.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-CML5XbavX0w.zh-CN.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.ja.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/17. Summary-1Gp4l-ZTCVk.ar.vtt
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Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-r5qca6q4Fn4.ja.vtt
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Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-tUeaXXT2oDI.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-mIzPoh_kqw4.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/21. Be Happy and Get Rid of Negatives-_ULZYGI6LPQ.zh-CN.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/32. Compute CI-nCg6F5QQZsI.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-hW_1ASU-j8A.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/23. Careful with Color-aKwXLGs0Rfs.zh-CN.vtt
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/21. Conclusion-UFwgr6tLcuI.ar.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/01. Intro to Creating Tables-mIIL-p2gaK4.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.ja.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.en.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/09. Data Types Summary-T-KrQoAJUpI.pt-BR.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess-mCZxHNB1u4w.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.ja.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-32WHsQi1UWc.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-y_Hp6nNKxdM.ar.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 3-oVGmi4zBOT8.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-Mt5TWGYacJs.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro-rR68JXwKBxE.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-q_zfkCwRg1w.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/47. Start Creating-Nr1w-Hxjld4.pt-BR.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.it.vtt
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/08. 24. Classical Music-3hSAWKrdO5s.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-S4KbzIyEwV8.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.en.vtt
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Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ujpjeaxE6GU.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.pt-BR.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.zh-CN.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision-tSZJDW3qp_I.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.ja.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.pt-BR.vtt
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Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.en-US.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/03. What Is Coming Up-oDJsnQcCPr4.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.ja.vtt
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Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3-o7LnSu0CEb4.ar.vtt
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Part 14-Module 01-Lesson 05_Analyzing Results/20. Course Conclusion-6aBIwp3n7_8.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.zh-CN.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/15. SD of Karma Points per Post-gIR0M2Jxb0k.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-9JHRpVTMuK4.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.ja.vtt
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Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-aseCJf5mrdo.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/28. Changing the Chart Type-wsjvZQaKIgA.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.th.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-JKZF4qHztv0.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/11. Bounds of Area-UPRiS4xRnow.pt-BR.vtt
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Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/05. Does Range Change-sCHCU42thsI.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-vxS-Kh4eI0U.ja.vtt
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Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.zh-CN.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs-KAOIExZuV_M.en.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/31. Lesson Conclusion-quP9Njc2aMg.en.vtt
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Introduction to Window Functions-u3qLjP8KMKc.en.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/16. Confidence Intervals And Hypothesis Tests-T2d9AUnWl-I.en.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/13. Line Plots-GsaBT47pjgQ.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/26. Rent - Cohen's d-admfaazbCnY.zh-CN.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/07. Google Account-7C3vCAVaPXo.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/07. Google Account-7C3vCAVaPXo.es.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds-WeS0ogG86nk.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-49B5hlxzTRc.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/11. Slope and Intercept-Ksn1g5fCe1I.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/25. Algorithms for Minimizing Squared Errors-Dw_9Dp6wcJ8.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-9DHPaCjg9HM.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.ar.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes-icmKCnOXQdI.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.pt-BR.vtt
902 Bytes
Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.zh-CN.vtt
902 Bytes
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.ar.vtt
902 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.ja.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-pUaHzMlfxrk.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/12. Define Outlier-7rLkGwsbMUY.en.vtt
901 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.ja.vtt
901 Bytes
Part 16-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion-xYqxZQmXCdI.pt-BR.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/11. Acne Medication-Xt2k2PWBwm4.pt-BR.vtt
900 Bytes
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.pt-BR.vtt
900 Bytes
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-Xrl2Hd--NWs.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-bgT8sWuV2lc.en.vtt
900 Bytes
Part 12-Module 02-Lesson 05_Trees/01. Trees-PXie7f22v2Q.en-US.vtt
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Part 12-Module 02-Lesson 08_Technical Interview - Python/06. Runtime Analysis-8bI9OgOB2qI.zh-CN.vtt
900 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-o_qyeIeRb_Y.ar.vtt
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Part 14-Module 01-Lesson 04_Designing an Experiment/25. Conclusion-YS4bR1vQ3Ls.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.ar.vtt
900 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.es-ES.vtt
900 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-bgT8sWuV2lc.en.vtt
900 Bytes
Part 05-Module 01-Lesson 05_Data Quality/01. Introduction-JA7oIPaf9PM.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.ja.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/25. Welcome to the End of Evaluation Lesson-sgFfl-j_oCs.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-3nZ2FL7C3sU.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-0OkHWvkwCus.zh-CN.vtt
898 Bytes
Part 13-Module 01-Lesson 04_Design Principles/02. Visual Encodings Recap-zyroaZ34ltA.en.vtt
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Part 16-Module 03-Lesson 02_SQL Joins/02. Why Not Store Everything in One Table-rvY4A6FpS40.en.vtt
898 Bytes
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/01. 26 Spread Part 1-zb76Z_viYLY.en.vtt
898 Bytes
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/09. Extra Practice With Dashboards-Va2zNfnUC6o.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-AnksTk1zI3Y.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.pt-BR.vtt
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Part 12-Module 02-Lesson 05_Trees/01. Trees-PXie7f22v2Q.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-n1EbdV_CTcc.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.zh-CN.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values--xVYQQHNNuM.zh-CN.vtt
896 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.pt-BR.vtt
896 Bytes
Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-_TJeoCTDykE.en.vtt
896 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.ar.vtt
896 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.zh-CN.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values--xVYQQHNNuM.zh-CN.vtt
896 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-6LgGDqQLpyc.zh-CN.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution-QjhQztBNz-Q.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/11. Generalize Point Estimate-i4lFgFq8Kpo.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI-llyWJTM8V5o.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.en-US.vtt
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Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.en.vtt
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Part 12-Module 02-Lesson 05_Trees/01. Trees-PXie7f22v2Q.pt-BR.vtt
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/01. Case Study Introduction-r8uEDyBylHY.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-CJ_C0FZBCPY.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/20. Equation for Average Deviation-dYbYjtCzQPo.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/15. The Benefits of Dimple-PkCeV9KNiMg.zh-CN.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.ar.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-mdCk7Gwkd4g.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.en.vtt
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Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/11. Slope and Intercept-Ksn1g5fCe1I.en.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.pt-BR.vtt
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/01. Introduction to Data Cleaning-YTtH3NM2BX0.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-_zx9cahSRNE.es.vtt
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Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-8vi9b_LHHz8.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics-meNSO42JF6I.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.es.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/24. Final Thoughts-CNGDocH1k3k.zh-CN.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/24. Changing the X-axis Interval-WwN3tYnOd8A.ar.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion-xYqxZQmXCdI.en.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/14. Cleaning For Quallity -qyixEwMRtWA.en.vtt
891 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma-NMnlSnu8DPI.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/16. Wrap Up-BGt2DQer6I4.en.vtt
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Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.pt-BR.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/32. Hypothesis Testing Conclusion-nQFchD4XPPs.zh-CN.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/01. 26 Spread Part 1-zb76Z_viYLY.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.es.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-CJ_C0FZBCPY.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/23. Wrap-Up-DZa6UOGet_g.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-vxS-Kh4eI0U.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-8QEAYYIyopY.zh-CN.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-WjRAjbeG0RE.en.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-8QEAYYIyopY.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-90OMETgfDyk.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-90OMETgfDyk.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-VdVjOC6UP6c.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-Xo3Le7VTZZM.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-tjEua8efugg.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/16. Charts Types and Design Elements-h2tIZuzMuQU.ar.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-aW9OOZKfqR8.zh-CN.vtt
887 Bytes
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.ja.vtt
887 Bytes
Part 17-Module 01-Lesson 12_Hypothesis Testing/16. How Do We Choose Between Hypotheses-JkXTwS-5Daw.zh-CN.vtt
887 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/07. Google Account-7C3vCAVaPXo.pt-BR.vtt
886 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.es.vtt
886 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/07. Google Account-7C3vCAVaPXo.pt-BR.vtt
886 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.es.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-VdVjOC6UP6c.pt-BR.vtt
886 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/36. Hypothesis Testing-GyLWb1FBJsA.en.vtt
886 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/34. Keyboards - SD of Differences--wbCbKqqaZY.zh-CN.vtt
886 Bytes
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Introduction to Window Functions-u3qLjP8KMKc.zh-CN.vtt
886 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.es-ES.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.ar.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/01. Effect Size-z98xODInLCQ.zh-CN.vtt
885 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.es-ES.vtt
885 Bytes
Part 21-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.ar.vtt
885 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/19. Finches - Decision-9N6i3RZun5A.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/24. Overfitting-plx_F2BkwNQ.zh-CN.vtt
884 Bytes
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.pt-BR.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/26. Recap-VM6GGNC2q8I.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.es.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/07. Chop Off the Tails-NmlhFjNHmXc.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means-AocpFl2wt6k.pt-BR.vtt
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/01. Lesson Overview-DkjRzNwjSfo.en.vtt
883 Bytes
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/01. Instructors Introduction-lIvm8urf4GE.zh-CN.vtt
883 Bytes
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.en.vtt
883 Bytes
Part 11-Module 01-Lesson 09_Clustering/13. Some challenges of k-means-e2CdlG5P4WA.ar.vtt
882 Bytes
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-AI9kNE00Los.ar.vtt
882 Bytes
Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-lK2lDLdE6iA.pt-BR.vtt
880 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.zh-CN.vtt
880 Bytes
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-WxAWorS2SLg.pt-BR.vtt
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/01. Lesson Introduction-nQBbywNKTVc.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.es-ES.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/20. Shoes - 95 CI-Ld7EaNyua4c.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.pt-BR.vtt
879 Bytes
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.en.vtt
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Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-5Uon6hUTl8Y.zh-CN.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/01. Introduction-2Y279421n3A.pt-BR.vtt
879 Bytes
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.en.vtt
879 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.en.vtt
879 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/20. Shoes - 95 CI-hN3Js3thgdY.pt-BR.vtt
878 Bytes
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1 Solution -Noykh9Zt6aI.en.vtt
878 Bytes
Part 18-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate -CDRmFJHywp8.zh-CN.vtt
878 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-_zx9cahSRNE.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/10. Calculate SDs-x-VMDl-3p7M.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision-pZu3Gr5cAUU.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/30. Conclusion-33thdy0IjPE.ar.vtt
876 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.en.vtt
876 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.ja.vtt
876 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.zh-CN.vtt
876 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.pt-BR.vtt
876 Bytes
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/17. Conclusion-D_ioSXAre1A.zh-CN.vtt
876 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/19. Null Hypothesis-Klv_8052hoA.zh-CN.vtt
875 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/38. World Cup Participation Animation-2GN_nwKc_ZA.zh-CN.vtt
875 Bytes
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/02. Download Tableau Public-2bXsg6SKHG8.en.vtt
875 Bytes
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/02. Download Tableau Public-2bXsg6SKHG8.en.vtt
875 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-ydpbvqLmLQI.pt-BR.vtt
874 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/15. Roll 1 Die-NHnIYEKcnUc.en.vtt
874 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width-TYN_LGAV3m8.ja.vtt
874 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.ja.vtt
874 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.en.vtt
874 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.ja.vtt
874 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6--LtbhZvwwM8.ar.vtt
874 Bytes
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.en.vtt
874 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NkyYCLoJVyE.zh-CN.vtt
873 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/37. Probability of Mean-RNgSdHPE4aA.en.vtt
873 Bytes
Part 04-Module 02-Lesson 01_Data Analysis Process/15. Getting Data from First Week -adqc5fF5B8Y.zh-CN.vtt
873 Bytes
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/01. Introduction-wwzSxJvGwf0.pt-BR.vtt
873 Bytes
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.pt-BR.vtt
873 Bytes
Part 13-Module 01-Lesson 01_Visualization Fundamentals/09. The Data Science Process-Kxp2TNV3n5k.zh-CN.vtt
873 Bytes
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/01. Introduction-wwzSxJvGwf0.pt-BR.vtt
873 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/07. Google Account-7C3vCAVaPXo.en.vtt
872 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/07. Google Account-7C3vCAVaPXo.en.vtt
872 Bytes
Part 06-Module 01-Lesson 01_Working with MongoDB/11. Multiple Field Queries-tsAh4HonzIw.zh-CN.vtt
872 Bytes
Part 06-Module 01-Lesson 01_Working with MongoDB/16. Operators-PlJ_dfdEbR0.zh-CN.vtt
872 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.pt-BR.vtt
872 Bytes
Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-F7PIJM0q524.ar.vtt
872 Bytes
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.ja.vtt
872 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.en.vtt
871 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.ja.vtt
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Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete--uRSI_oybJQ.en.vtt
871 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/13. Match Boxplots-xg4WOp3v-CM.zh-CN.vtt
870 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/31. Raining-UNASgS676Hc.pt-BR.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/11. Enron Dataset Mini-Project Video-0zGp5er3fy4.zh-CN.vtt
870 Bytes
Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.zh-CN.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.es-ES.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/21. Great Job!-fm66AGJzRI0.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/02. Accuracy Review-g3sxDtlGlAM.ar.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 3-oVGmi4zBOT8.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.ar.vtt
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Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ujpjeaxE6GU.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.en-GB.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/32. Location of Mean on Distribution-k3RUgrtFIl4.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-bgT8sWuV2lc.pt-BR.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-bgT8sWuV2lc.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-wBduq7St2Ak.es.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs-PXHHbaYnciY.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.it.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-0X7voyhbZ8k.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.en.vtt
865 Bytes
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.ar.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/25. Changing Bin Size-fI_SYnWB1XA.zh-CN.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/04. Total Number of Samples-q5JgPXsHSrA.zh-CN.vtt
864 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.ar.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance--5--eKjgU7k.ar.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.pt-BR.vtt
864 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/10. Report CI Results 2-eVTzjsolEwI.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.pt-BR.vtt
863 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.zh-CN.vtt
863 Bytes
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-3FO2y4tlZ3A.ar.vtt
863 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-XCf2FDdHDGs.es.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject-K2OncV6Bzo8.en.vtt
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/06. Write the Conclusion-i3ozyhGPmIg.pt-BR.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-JZx1Pyzuo_s.zh-CN.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-1lNAvDubBfI.zh-CN.vtt
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/07. Traveling Salesman Problem-9ruR5Ux63QU.zh-CN.vtt
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Part 21-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI-fFY4isvV-Sk.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/28. Probability of Obtaining Mean-00SWFc0sFIg.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/25. Algorithms for Minimizing Squared Errors-Dw_9Dp6wcJ8.en.vtt
861 Bytes
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Measures of Center - The Mode-NE81NZgECqg.ar.vtt
861 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.es.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/15. SD of Karma Points per Post-gIR0M2Jxb0k.en.vtt
860 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/10. 95 CI with Exact Z-Scores-Ipj62kdE3Lo.zh-CN.vtt
860 Bytes
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-mIn7nMR092Q.zh-CN.vtt
860 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.zh-CN.vtt
860 Bytes
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-mIn7nMR092Q.zh-CN.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-nu2OKJwDvvE.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.zh-CN.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-fpPPozvkpWM.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.zh-CN.vtt
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Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-r5qca6q4Fn4.en.vtt
857 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width-TYN_LGAV3m8.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/01. Intro to the PDF-QTVWqk09q1A.pt-BR.vtt
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Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-4Fkfu37el_k.pt-BR.vtt
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Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-Fi3uuGj8bhs.pt-BR.vtt
856 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/27. Rent - CI-QXFudvtcjv0.en.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/01. Introduction to Lesson 5-l2Nab0LY_cI.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-GGCzMmOpQqQ.zh-CN.vtt
855 Bytes
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-4Fkfu37el_k.en.vtt
855 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-cUlEryXX9BM.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-pUaHzMlfxrk.es.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare-B2KnUg5iz0Y.ar.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion-xYqxZQmXCdI.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.hr.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/07. Sampling Distribution-7tlVeUW2t7Q.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio-XtDLvgt7LQk.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-omL8MVZjLts.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.ja.vtt
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Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-PRjmvj6Vubs.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/01. Animation and Interaction-4aBXHspd7WI.zh-CN.vtt
853 Bytes
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/14. Performance Tuning Motivation-aY4_uYWEuoE.zh-CN.vtt
852 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.ja.vtt
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Part 17-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-PRQDaHphZhw.zh-CN.vtt
850 Bytes
Part 11-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project-JEK7-ocWu0M.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-j2SP83afRS0.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.es-ES.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.ar.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-Xo3Le7VTZZM.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-nRurXCTYxG4.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR-sl51Cpwy5RA.en.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-kIITzFRh5mQ.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.pt-BR.vtt
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/01. Case Study Introduction-r8uEDyBylHY.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-aseCJf5mrdo.zh-CN.vtt
849 Bytes
Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-BGNx2FiNFY0.ar.vtt
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Part 18-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate -CDRmFJHywp8.en.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/01. 26 Spread Part 1-zb76Z_viYLY.zh-CN.vtt
848 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.pt-BR.vtt
848 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/20. Shoes - 95 CI-hN3Js3thgdY.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.ja.vtt
847 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.zh-CN.vtt
847 Bytes
Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-zTI5Ci5WWzM.en.vtt
847 Bytes
Part 16-Module 03-Lesson 03_SQL Aggregations/09. MIN MAX-1ewVsgWUih8.pt-BR.vtt
847 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-PYNWtLgtRfU.ar.vtt
846 Bytes
Part 13-Module 01-Lesson 01_Visualization Fundamentals/25. Transition to Tech Portion-WovqufP4nk0.ar.vtt
846 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.ja.vtt
846 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/22. SEM-gl4ogBY9AOI.zh-CN.vtt
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Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-r5qca6q4Fn4.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.ja.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.es-ES.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-lK2lDLdE6iA.en.vtt
844 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/28. Avg. Squared Dev. in Words-kgc_y-oJObM.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/11. Two-Tailed Test-4fWHT1f72B8.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-si8AcC5pTfM.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.ar.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-si8AcC5pTfM.zh-CN.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-IJZs7KARtFo.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-IJZs7KARtFo.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/01. Compare Sample Means-QheTapjHFdU.en.vtt
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Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.ja.vtt
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Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-tUeaXXT2oDI.zh-CN.vtt
842 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.ar.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-zAQygY7v2Ds.ar.vtt
842 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/33. Advantages with CSS-lCTey7ryZ1A.zh-CN.vtt
842 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/47. Start Creating-Nr1w-Hxjld4.zh-CN.vtt
842 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-Ig82ol_4Lgo.en.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/23. Convert to Z-Score-UAHkVUloKbg.zh-CN.vtt
841 Bytes
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-xSQTzAeeoEc.ar.vtt
841 Bytes
Part 14-Module 01-Lesson 01_Overview of AB Testing/27. Making Decisions about Uncertain Data-GM8MV0FvCUo.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.ja.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.pt-BR.vtt
840 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/12. Define Outlier-7rLkGwsbMUY.zh-CN.vtt
840 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.en.vtt
840 Bytes
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-VERLCqDewrM.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/23. Wrap-Up-DZa6UOGet_g.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-TIs9j-QITxw.pt-BR.vtt
839 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-pUaHzMlfxrk.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/39. Keyboards - CI for Dependent Samples-83VGOXwmjUw.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-gydx9-h1liU.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.ar.vtt
838 Bytes
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-Ee2o-0arldg.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/28. Probability of Obtaining Mean-00SWFc0sFIg.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables-08GsrEIOP9Q.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.en.vtt
837 Bytes
Part 11-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.zh-CN.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/13. Feature Scaling Mini-Project Video-e6zbTFctnJU.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/22. Narratives Summary-QFXxRlLETyI.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.es-ES.vtt
837 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.it.vtt
837 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/30. Standard Deviation-0seYYIPBXxI.zh-CN.vtt
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Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.ar.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/01. Introduction-2Y279421n3A.en.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.es.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-9JHRpVTMuK4.ko.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.ar.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.ja.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-IJZs7KARtFo.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-IJZs7KARtFo.es.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-8LDZzqrCnS0.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.zh-CN.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.ja.vtt
834 Bytes
Part 16-Module 03-Lesson 02_SQL Joins/02. Why Not Store Everything in One Table-rvY4A6FpS40.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-wBduq7St2Ak.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-nRurXCTYxG4.es.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic-htd-vu8q3po.en.vtt
832 Bytes
Part 05-Module 02-Lesson 03_Elements of SQL/16. Wrap Up-BGt2DQer6I4.zh-CN.vtt
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/06. Write the Conclusion-i3ozyhGPmIg.es-MX.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/13. Feature Scaling Mini-Project Video-e6zbTFctnJU.pt-BR.vtt
832 Bytes
Part 13-Module 01-Lesson 04_Design Principles/34. Determining a Graphic's Effectiveness-BZERcWwQ-PM.pt-BR.vtt
832 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.it.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.zh-CN.vtt
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/08. 24. Classical Music-3hSAWKrdO5s.es.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/12. Ratio of SDs-L4Jgcf9FNKA.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.zh-CN.vtt
830 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.ja.vtt
830 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.pt-BR.vtt
830 Bytes
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.ar.vtt
830 Bytes
Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-mpYpT6nZVEo.pt-BR.vtt
830 Bytes
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-WjRAjbeG0RE.zh-CN.vtt
830 Bytes
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1 Solution -Noykh9Zt6aI.zh-CN.vtt
830 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean--IGW7WH6CIA.zh-CN.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision-tSZJDW3qp_I.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.zh-CN.vtt
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Aliases for Multiple Window Functions-RWe03bULYnM.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.ar.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-6yT3SlcmTl8.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05-TyqZdKR8J_w.en.vtt
828 Bytes
Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables-08GsrEIOP9Q.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-c1gvsNx_ypg.pt-BR.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.en.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-E55ujT-kf5E.pt-BR.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/09. Data Types Summary-T-KrQoAJUpI.en.vtt
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Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.zh-CN.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.ja.vtt
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/12. Congratulations!-sCQ7ZViODaw.ar.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/07. Sampling Distribution-7tlVeUW2t7Q.zh-CN.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/18. Roll 5 Dice-BgBEqvjLNig.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.ja.vtt
827 Bytes
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-E55ujT-kf5E.en.vtt
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Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-_TJeoCTDykE.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/28. Changing the Chart Type-wsjvZQaKIgA.zh-CN.vtt
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Aliases for Multiple Window Functions-RWe03bULYnM.en.vtt
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Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.en.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-AnksTk1zI3Y.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/01. Intro to Creating Tables-mIIL-p2gaK4.zh-CN.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-omL8MVZjLts.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.en-US.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/01. Introduction to Advanced SQL-i0VaVPIKUks.pt-BR.vtt
825 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/20. Standard Error When n Increases-dU3LgB8i6XM.pt-BR.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic-0iKPoKeApJI.en.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-CZnFt1rOfwc.ar.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-4Ywln5AT6Hc.zh-CN.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/14. Confidence Intervals-fDkfHKODOcQ.zh-CN.vtt
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Part 16-Module 03-Lesson 03_SQL Aggregations/09. MIN MAX-1ewVsgWUih8.en.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.es-ES.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-gUXB5GofFKM.zh-CN.vtt
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Part 05-Module 01-Lesson 05_Data Quality/06. Difficulty of Quality Metrics-uqCSn9Q9ARk.zh-CN.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/25. NEW Create a Radius Scale-SUj-uKarNt0.en-US.vtt
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/08. CONCAT-bCxZnQN28Y4.ar.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/06. Mark Z the Outlier-SADDVcUMQXM.pt-BR.vtt
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Part 11-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project-JEK7-ocWu0M.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/54. Use Variables Wisely-j8o2WUo3-Xg.zh-CN.vtt
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic-0iKPoKeApJI.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.ja.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.en.vtt
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Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.ar.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NTyY1HlXhiQ.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center-bsybN1HIH4s.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-AnksTk1zI3Y.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/25. NEW Create a Radius Scale-SUj-uKarNt0.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-HFCs3LbQ5Z0.ar.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.ja.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.ja.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.en-US.vtt
818 Bytes
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-K4gGK4ScT7M.zh-CN.vtt
818 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/26. Evaluation Mini-Project Video-s13K9G1VaWM.zh-CN.vtt
818 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/27. The Update Function-z5f-oK0jwZk.pt-BR.vtt
818 Bytes
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.zh-CN.vtt
817 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.zh-CN.vtt
817 Bytes
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-xYxD4GD1woo.en.vtt
817 Bytes
Part 12-Module 02-Lesson 01_Introduction and Efficiency/04. Syntax-08M93RaBSgU.pt-BR.vtt
817 Bytes
Part 13-Module 01-Lesson 04_Design Principles/34. Determining a Graphic's Effectiveness-BZERcWwQ-PM.en.vtt
817 Bytes
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.zh-CN.vtt
817 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.es-ES.vtt
817 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05-oCQnqFE4uxQ.zh-CN.vtt
816 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.en.vtt
816 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.ja.vtt
816 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.ar.vtt
816 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.ar.vtt
816 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.ar.vtt
816 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error-w-7MoreKqaU.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.en.vtt
815 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-T5TBKcjzleI.pt-BR.vtt
814 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/20. Equation for Average Deviation-dYbYjtCzQPo.zh-CN.vtt
814 Bytes
Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-yLeLxDyXCSY.pt-BR.vtt
814 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.zh-CN.vtt
814 Bytes
Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-_TJeoCTDykE.zh-CN.vtt
814 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes-FxF9WyIPFbo.pt-BR.vtt
813 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-Och80L_uNjU.ja.vtt
813 Bytes
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.en.vtt
813 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.th.vtt
813 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.ja.vtt
813 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-ZwMY5rAAd7Q.ar.vtt
812 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.zh-CN.vtt
812 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.pt-BR.vtt
812 Bytes
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.ja.vtt
812 Bytes
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-4Fkfu37el_k.zh-CN.vtt
812 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-bgT8sWuV2lc.zh-CN.vtt
812 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-bgT8sWuV2lc.zh-CN.vtt
812 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.en.vtt
811 Bytes
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/01. Lesson Overview-DkjRzNwjSfo.zh-CN.vtt
811 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.en.vtt
810 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.pt-BR.vtt
810 Bytes
Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-TIs9j-QITxw.en.vtt
810 Bytes
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.zh-CN.vtt
810 Bytes
Part 18-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python -cUmcLjWgxwM.ar.vtt
810 Bytes
Part 21-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.pt-BR.vtt
810 Bytes
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/01. Introduction-wwzSxJvGwf0.en.vtt
809 Bytes
Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-0X7voyhbZ8k.zh-CN.vtt
809 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.pt-BR.vtt
809 Bytes
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/01. Introduction-wwzSxJvGwf0.en.vtt
809 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.zh-CN.vtt
808 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.zh-CN.vtt
808 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-lK2lDLdE6iA.es.vtt
808 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.en.vtt
808 Bytes
Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-zTI5Ci5WWzM.zh-CN.vtt
808 Bytes
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-IC47yHGmgMk.en.vtt
808 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/09. Between 118 and 226-pHNtOrr6bgE.zh-CN.vtt
807 Bytes
Part 05-Module 02-Lesson 01_Data and Tables/11. Favorite Animals-O7kWdC8ffEw.en.vtt
807 Bytes
Part 13-Module 01-Lesson 04_Design Principles/02. Visual Encodings Recap-zyroaZ34ltA.zh-CN.vtt
807 Bytes
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Window Functions Conclusion-2ZdocDMw7D8.ar.vtt
807 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-0plipvHyAlk.zh-CN.vtt
806 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-IJZs7KARtFo.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-0plipvHyAlk.zh-CN.vtt
806 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-IJZs7KARtFo.en.vtt
806 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.ja.vtt
806 Bytes
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-IC47yHGmgMk.pt-BR.vtt
806 Bytes
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.zh-CN.vtt
806 Bytes
Part 21-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.en.vtt
806 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/09. Sampling Distribution-XUA8rsit0J4.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.ja.vtt
805 Bytes
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-PRjmvj6Vubs.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.en-GB.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.pt-BR.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/20. Congrats-quszTmIRG8M.en.vtt
803 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.en.vtt
803 Bytes
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview-2X8GJyZUlDo.en.vtt
803 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Im9nOwm_fS8.pt-BR.vtt
802 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-hW_1ASU-j8A.zh-CN.vtt
802 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.pt-BR.vtt
802 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.pt-BR.vtt
802 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.ar.vtt
802 Bytes
Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-xJtmPbEfpFo.zh-CN.vtt
801 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.zh-CN.vtt
799 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.zh-CN.vtt
799 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.ar.vtt
799 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.zh-CN.vtt
799 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.en.vtt
799 Bytes
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.ar.vtt
799 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-JKZF4qHztv0.zh-CN.vtt
798 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.en.vtt
798 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.pt-BR.vtt
798 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.en.vtt
798 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-Ig82ol_4Lgo.zh-CN.vtt
797 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD-1SL8FGhaKqA.en.vtt
797 Bytes
Part 11-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.pt-BR.vtt
797 Bytes
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.zh-CN.vtt
797 Bytes
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-WxAWorS2SLg.en.vtt
797 Bytes
Part 14-Module 01-Lesson 04_Designing an Experiment/25. Conclusion-YS4bR1vQ3Ls.zh-CN.vtt
797 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.it.vtt
797 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.pt-BR.vtt
797 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/05. Critical Values 0.001-h72200GCyaI.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-VdVjOC6UP6c.es.vtt
794 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test-zqj1NZbe5os.pt-BR.vtt
794 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-Och80L_uNjU.pt-BR.vtt
794 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-bRhdim9PTFI.ar.vtt
794 Bytes
Part 16-Module 02-Lesson 01_The Data Analysis Process/19. Exploring Data With Visuals-0i_9t4Wi0Og.pt-BR.vtt
794 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/02. Alpha Levels-VuEwqXDd1Rs.zh-CN.vtt
793 Bytes
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.ar.vtt
793 Bytes
Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-FY9_6rOPk6c.zh-CN.vtt
793 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-cUlEryXX9BM.en.vtt
793 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/17. Finches - Mean and s-XhVy8ALgO0U.en.vtt
792 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.en.vtt
792 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.ja.vtt
792 Bytes
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Introduction to Percentiles-t7SX2ZEdxKA.pt-BR.vtt
792 Bytes
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.hr.vtt
792 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/07. More Detail-E931DQC0hno.pt-BR.vtt
791 Bytes
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/06. Write the Conclusion-i3ozyhGPmIg.en.vtt
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Part 11-Module 01-Lesson 16_Tying It All Together/03. End of Content-MFRkl-aXL8I.zh-CN.vtt
791 Bytes
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-AI9kNE00Los.pt-BR.vtt
791 Bytes
Part 13-Module 01-Lesson 04_Design Principles/39. Junk Yard-2CT21UEcGQk.ar.vtt
791 Bytes
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-FdRVdkASudw.zh-CN.vtt
791 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-90OMETgfDyk.en.vtt
790 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-90OMETgfDyk.en.vtt
790 Bytes
Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-zTI5Ci5WWzM.pt-BR.vtt
790 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.en.vtt
790 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.en.vtt
790 Bytes
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import Solution-QnTPEAGXJaE.ar.vtt
790 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-XCf2FDdHDGs.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/01. Intro to the PDF-QTVWqk09q1A.en.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.en.vtt
789 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.en.vtt
788 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-8LDZzqrCnS0.en.vtt
788 Bytes
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download-a5o3ck1bxEs.pt-BR.vtt
788 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI-diHsJPQHtKc.zh-CN.vtt
787 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.en.vtt
787 Bytes
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Aliases for Multiple Window Functions-RWe03bULYnM.zh-CN.vtt
787 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction-FGbxq1hQgtk.ar.vtt
787 Bytes
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.zh-CN.vtt
787 Bytes
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/08. 24. Classical Music-3hSAWKrdO5s.en.vtt
786 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-t0yIetl9ZxI.es.vtt
786 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-ydpbvqLmLQI.en.vtt
786 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/32. Compute CI-nCg6F5QQZsI.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-_zx9cahSRNE.zh-CN.vtt
785 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/11. Bounds of Area-UPRiS4xRnow.en.vtt
785 Bytes
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/15. Standardizing Each Column Again-7NofF-s1UGY.pt-BR.vtt
785 Bytes
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview-2X8GJyZUlDo.zh-CN.vtt
785 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.zh-CN.vtt
785 Bytes
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/15. Standardizing Each Column Again-7NofF-s1UGY.pt-BR.vtt
785 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-t0yIetl9ZxI.en.vtt
784 Bytes
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-0ZBp8oWySAc.ar.vtt
784 Bytes
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/12. What Can You Create In Tableau-gNqIvf5iJA8.zh-CN.vtt
784 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/07. Chop Off the Tails-NmlhFjNHmXc.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-9JHRpVTMuK4.en.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.zh-CN.vtt
783 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.ja.vtt
783 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.ar.vtt
783 Bytes
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.zh-CN.vtt
783 Bytes
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/21. Conclusion-UFwgr6tLcuI.pt-BR.vtt
783 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.ar.vtt
783 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/07. Google Account-7C3vCAVaPXo.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/07. Google Account-7C3vCAVaPXo.zh-CN.vtt
782 Bytes
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Introduction to Percentiles-t7SX2ZEdxKA.en.vtt
782 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-kjk--LHqtCw.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/13. Two-Tailed Critical Values 0.01-Fzich-V7ZO0.pt-BR.vtt
781 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/11. Acne Medication-Xt2k2PWBwm4.en.vtt
781 Bytes
Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete--uRSI_oybJQ.zh-CN.vtt
781 Bytes
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-lS5DfbsWH34.pt-BR.vtt
781 Bytes
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/19. Congratulations!-_FPpbuuW-1o.en.vtt
781 Bytes
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-Ee2o-0arldg.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/31. Raining-UNASgS676Hc.en.vtt
780 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.zh-CN.vtt
780 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-P46v39eNSqM.pt-BR.vtt
780 Bytes
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.zh-CN.vtt
780 Bytes
Part 17-Module 01-Lesson 13_Case Study AB tests/14. Analyzing Multiple Metrics-DtZghKNa7Ak.pt-BR.vtt
780 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR-sl51Cpwy5RA.zh-CN.vtt
779 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs-PXHHbaYnciY.en.vtt
779 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/21. Standard Normal Distribution-5B-vrhyedws.pt-BR.vtt
779 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.zh-CN.vtt
779 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.th.vtt
779 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/15. Roll 1 Die-NHnIYEKcnUc.zh-CN.vtt
778 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/05. Critical Values 0.001-AdLGLYYYVao.en.vtt
778 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.zh-CN.vtt
778 Bytes
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.zh-CN.vtt
778 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.zh-CN.vtt
778 Bytes
Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-Fi3uuGj8bhs.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-eVAEO2QRdM0.ar.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/16. Outro-dps7Ti6Lado.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.th.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.es-ES.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means-AocpFl2wt6k.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/30. r^2-mnfgAsAVaTQ.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-P46v39eNSqM.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.en.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/09. Data Types Summary-T-KrQoAJUpI.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.es-ES.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-bnwLadF8gKo.ar.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-TpVxnYcI_uw.ar.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.pt-BR.vtt
774 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/27. Rent - CI-QXFudvtcjv0.zh-CN.vtt
773 Bytes
Part 05-Module 02-Lesson 01_Data and Tables/11. Favorite Animals-O7kWdC8ffEw.pt-BR.vtt
773 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.pt-BR.vtt
773 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.en.vtt
773 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.zh-CN.vtt
773 Bytes
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-R6oIvdBtsZw.pt-BR.vtt
773 Bytes
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-Njbmexuo7fo.ar.vtt
773 Bytes
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/31. Lesson Conclusion-quP9Njc2aMg.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.pt-BR.vtt
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Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-lS5DfbsWH34.en.vtt
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Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.th.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NTyY1HlXhiQ.es.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/12. Using the Z-Table-EeT7osOfzJE.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-q23Nlo1Rfn4.ar.vtt
771 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/14. Increase t-tBk_gBWan8k.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.ar.vtt
770 Bytes
Part 11-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.en.vtt
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Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete--uRSI_oybJQ.pt-BR.vtt
770 Bytes
Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-mpYpT6nZVEo.en.vtt
770 Bytes
Part 12-Module 02-Lesson 01_Introduction and Efficiency/04. Syntax-08M93RaBSgU.en-US.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/33. Highlight Countries-wjUenfTcSG0.pt-BR.vtt
770 Bytes
Part 11-Module 01-Lesson 07_Regressions/24. Minimizing Sum of Squared Errors-E1XzT619Eug.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.pt-BR.vtt
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Part 17-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.pt-BR.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects-OxL-gMTizUA.ar.vtt
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Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-R6oIvdBtsZw.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.th.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs-KAOIExZuV_M.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely-oIFRsiD2mQE.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject-K2OncV6Bzo8.zh-CN.vtt
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Part 12-Module 02-Lesson 01_Introduction and Efficiency/04. Syntax-08M93RaBSgU.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.it.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NTyY1HlXhiQ.en.vtt
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Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-VERLCqDewrM.en.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-xYxD4GD1woo.pt-BR.vtt
766 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD-UbnrfnB8vcs.pt-BR.vtt
765 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.ja.vtt
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Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-udJvijJvs1M.pt-BR.vtt
765 Bytes
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.ar.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.pt-PT.vtt
765 Bytes
Part 11-Module 01-Lesson 07_Regressions/25. Algorithms for Minimizing Squared Errors-Dw_9Dp6wcJ8.zh-CN.vtt
764 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.it.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/13. SD of Sampling Distribution-tPVKll2xFUw.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/11. Generalize Point Estimate-i4lFgFq8Kpo.zh-CN.vtt
763 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/20. Alternative Hypothesis-EH59aCNpHS8.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.ja.vtt
763 Bytes
Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-TIs9j-QITxw.zh-CN.vtt
763 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.zh-CN.vtt
763 Bytes
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download-a5o3ck1bxEs.en.vtt
763 Bytes
Part 21-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.en.vtt
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Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.ja.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.en-US.vtt
761 Bytes
Part 11-Module 01-Lesson 07_Regressions/11. Slope and Intercept-Ksn1g5fCe1I.zh-CN.vtt
761 Bytes
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-O5B-Z5SUoc8.ar.vtt
761 Bytes
Part 16-Module 03-Lesson 02_SQL Joins/02. Why Not Store Everything in One Table-rvY4A6FpS40.zh-CN.vtt
761 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.pt-BR.vtt
761 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/10. Two-Tailed t-Test-zlHtHBeJhww.pt-BR.vtt
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Part 08-Module 01-Lesson 01_Conduct a Job Search/04. Open Yourself Up to Opportunity-1OamTNkk1xM.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.ja.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes-FxF9WyIPFbo.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.en.vtt
759 Bytes
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.en-US.vtt
759 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores-8XZqX03Y6Vk.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value-qrN5FQdm9uA.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.ja.vtt
758 Bytes
Part 11-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!-UjaFiRdHPZg.pt-BR.vtt
758 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.en.vtt
757 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-c1gvsNx_ypg.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.es-ES.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test-bD9ULWEsW0M.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values-kNsdYqgn9Mk.pt-BR.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/02. Action Time-80DSWU8ZUoQ.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.en.vtt
756 Bytes
Part 17-Module 01-Lesson 14_Regression/01. Regression Introduction-PKqSS0TzXeA.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/20. Alternative Hypothesis-EH59aCNpHS8.en.vtt
754 Bytes
Part 05-Module 01-Lesson 03_Data in More Complex Formats/10. Intro to Screen Scraping-RJyVIgUUemE.pt-BR.vtt
754 Bytes
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-VERLCqDewrM.zh-CN.vtt
754 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-fpPPozvkpWM.zh-CN.vtt
754 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.en.vtt
754 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/37. Probability of Mean-RNgSdHPE4aA.zh-CN.vtt
753 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely-oIFRsiD2mQE.zh-CN.vtt
753 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/11. Bounds of Area-eADm6bXU3_0.pt-BR.vtt
753 Bytes
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.pt-BR.vtt
753 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.pt-BR.vtt
753 Bytes
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-Ee2o-0arldg.es.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-yLeLxDyXCSY.en.vtt
752 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.zh-CN.vtt
752 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.zh-CN.vtt
752 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.en.vtt
752 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.ar.vtt
752 Bytes
Part 01-Module 01-Lesson 01_Nanodegree Orientation/02. Introduction-fxNSn63xFvA.ar.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/36. Hypothesis Testing-GyLWb1FBJsA.zh-CN.vtt
751 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/09. Report CI Results-pr-2ZaCDzPY.en.vtt
751 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.ar.vtt
751 Bytes
Part 11-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!-UjaFiRdHPZg.en.vtt
751 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.zh-CN.vtt
751 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-8LDZzqrCnS0.es.vtt
750 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-t0yIetl9ZxI.pt-BR.vtt
750 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/12. Using the Z-Table-EeT7osOfzJE.en.vtt
750 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI-llyWJTM8V5o.zh-CN.vtt
750 Bytes
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-P1NzBPnfl2E.pt-BR.vtt
750 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.zh-CN.vtt
750 Bytes
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.zh-CN.vtt
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Part 17-Module 01-Lesson 14_Regression/21. Recap-DzMi27LI5l4.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/10. IQR-9dYN_oIly9I.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/09. Sampling Distribution-XUA8rsit0J4.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.zh-CN.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 -aEGtqoWIJIc.pt-BR.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/30. r^2-mnfgAsAVaTQ.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.zh-CN.vtt
748 Bytes
Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.zh-CN.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.hr.vtt
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Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.es-ES.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.ja.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-pUaHzMlfxrk.zh-CN.vtt
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Part 06-Module 01-Lesson 03_Analyzing Data/20. Congrats-quszTmIRG8M.pt-BR.vtt
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Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-r5qca6q4Fn4.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.en.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-n7gp8USw0Jw.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-q_zfkCwRg1w.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/33. Highlight Countries-wjUenfTcSG0.en.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.ar.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.pt-BR.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/21. Standard Normal Distribution-5B-vrhyedws.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test-zqj1NZbe5os.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.es-ES.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.es-ES.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download Solution-SDqdLhgsBNc.pt-BR.vtt
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Part 21-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.pt-BR.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/05. SD for Meal Price-PPcSvB1htPc.en.vtt
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Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-20QVVrTcp2A.ar.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.zh-CN.vtt
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Part 17-Module 01-Lesson 13_Case Study AB tests/18. Conclusion-qmGjRpMVBz8.pt-BR.vtt
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Part 21-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/13. Two-Tailed Critical Values 0.01-Fzich-V7ZO0.en.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/23. Wrap-Up-DZa6UOGet_g.zh-CN.vtt
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Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-R6oIvdBtsZw.zh-CN.vtt
744 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/32. Location of Mean on Distribution-k3RUgrtFIl4.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/17. Finches - Mean and s-XhVy8ALgO0U.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/10. Intro to Screen Scraping-RJyVIgUUemE.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.zh-CN.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-PlFG87qPSB4.pt-BR.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-zAQygY7v2Ds.pt-BR.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-HH73nOnzRrc.ar.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD-1SL8FGhaKqA.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables-08GsrEIOP9Q.zh-CN.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.zh-CN.vtt
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Part 12-Module 02-Lesson 05_Trees/01. Trees-PXie7f22v2Q.zh-CN.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-J2L_ZU-YMxc.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-OVoEIInUg9A.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/27. The Update Function-z5f-oK0jwZk.en.vtt
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Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.it.vtt
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Part 17-Module 01-Lesson 11_Confidence Intervals/16. Confidence Intervals And Hypothesis Tests-T2d9AUnWl-I.zh-CN.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/20. You Can Iterate-ZU8EnPbR-pk.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-TE2BZql64XY.pt-BR.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/19. Congratulations!-_FPpbuuW-1o.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.es-ES.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR-o2n0nea_1T0.pt-BR.vtt
740 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/01. Compare Sample Means-QheTapjHFdU.zh-CN.vtt
740 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI-fFY4isvV-Sk.en.vtt
740 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/20. Shoes - 95 CI-Ld7EaNyua4c.zh-CN.vtt
740 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above-lGHZ4w8UqIk.en.vtt
739 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.pt-BR.vtt
739 Bytes
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.ar.vtt
739 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-y_Hp6nNKxdM.pt-BR.vtt
739 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-783QmxtIx58.pt-BR.vtt
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-E55ujT-kf5E.zh-CN.vtt
739 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.ar.vtt
738 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.en.vtt
738 Bytes
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.pt-BR.vtt
737 Bytes
Part 13-Module 01-Lesson 07_Narrative Structures/34. Updated World Cup Data Set-tA_je-rSL7c.ar.vtt
737 Bytes
Part 16-Module 03-Lesson 05_SQL Data Cleaning/08. CONCAT-bCxZnQN28Y4.pt-BR.vtt
737 Bytes
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 2-so5zydnbYEg.pt-BR.vtt
737 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD-UbnrfnB8vcs.en.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-yLeLxDyXCSY.zh-CN.vtt
736 Bytes
Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.pt-BR.vtt
736 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-q_zfkCwRg1w.en.vtt
736 Bytes
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/01. Introduction-2Y279421n3A.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.pt-BR.vtt
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/26. Recap-VM6GGNC2q8I.zh-CN.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.en.vtt
736 Bytes
Part 06-Module 01-Lesson 03_Analyzing Data/20. Congrats-quszTmIRG8M.zh-CN.vtt
735 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.ja.vtt
735 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.pt-BR.vtt
735 Bytes
Part 17-Module 01-Lesson 13_Case Study AB tests/01. Case Study Introduction-J5uvdPxHIfs.pt-BR.vtt
735 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/28. Rent - Find CI-1bXAy-6Pxf0.pt-BR.vtt
734 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.en.vtt
734 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above-lGHZ4w8UqIk.pt-BR.vtt
733 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic-y1QSAIUlupg.pt-BR.vtt
733 Bytes
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/15. Standardizing Each Column Again-7NofF-s1UGY.en.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.zh-CN.vtt
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Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-z2R5CqjXrkA.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/15. Standardizing Each Column Again-7NofF-s1UGY.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/11. Favorite Animals-O7kWdC8ffEw.zh-CN.vtt
732 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.en.vtt
732 Bytes
Part 11-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project-JEK7-ocWu0M.zh-CN.vtt
732 Bytes
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-AI9kNE00Los.en.vtt
732 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-CJ_C0FZBCPY.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-kjk--LHqtCw.es-ES.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/28. Rent - Find CI-EZTRb9VBqAc.pt-BR.vtt
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/17. Data Cleaning Conclusion-KkHqnvD9BWY.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.ar.vtt
731 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5-HbS35vDe_x0.pt-BR.vtt
730 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-y_Hp6nNKxdM.en.vtt
730 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-783QmxtIx58.en.vtt
730 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.ja.vtt
730 Bytes
Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-dHS0BtLFTSQ.pt-BR.vtt
729 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-Och80L_uNjU.en.vtt
729 Bytes
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.th.vtt
729 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.es-ES.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-a1sLkQtfUKc.es.vtt
728 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5-HbS35vDe_x0.en.vtt
728 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/11. Two-Tailed Test-4fWHT1f72B8.en.vtt
728 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.pt-BR.vtt
728 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.en.vtt
728 Bytes
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.pt-BR.vtt
728 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.es-ES.vtt
728 Bytes
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download Solution-SDqdLhgsBNc.en.vtt
728 Bytes
Part 05-Module 01-Lesson 03_Data in More Complex Formats/10. Intro to Screen Scraping-RJyVIgUUemE.en.vtt
727 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.ja.vtt
727 Bytes
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/16. Subquery Conclusion-TUYvx2K9-5k.ar.vtt
727 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-Jbqf8OBORDg.ar.vtt
726 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-Jbqf8OBORDg.ar.vtt
726 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/02. Mean of Treated Population-ecy3VY8eNGM.pt-BR.vtt
724 Bytes
Part 21-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-XCf2FDdHDGs.zh-CN.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/16. Outro-dps7Ti6Lado.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.zh-CN.vtt
723 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.th.vtt
723 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely-oIFRsiD2mQE.pt-BR.vtt
722 Bytes
Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-5dt0N4XN-y4.en.vtt
722 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-cUlEryXX9BM.zh-CN.vtt
722 Bytes
Part 16-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data-AJF5smH1TJU.ar.vtt
722 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-wBduq7St2Ak.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-BbJfVyCm21o.ar.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/15. Standardizing Each Column Again-7NofF-s1UGY.zh-CN.vtt
720 Bytes
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-WxAWorS2SLg.zh-CN.vtt
720 Bytes
Part 13-Module 01-Lesson 04_Design Principles/34. Determining a Graphic's Effectiveness-BZERcWwQ-PM.zh-CN.vtt
720 Bytes
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/15. Standardizing Each Column Again-7NofF-s1UGY.zh-CN.vtt
720 Bytes
Part 05-Module 02-Lesson 01_Data and Tables/17. Summary-1Gp4l-ZTCVk.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-Kn9v0KGDsvc.ar.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 -aEGtqoWIJIc.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/10. Two-Tailed t-Test-zlHtHBeJhww.en.vtt
718 Bytes
Part 13-Module 01-Lesson 04_Design Principles/44. Leland Wilkinson-w7TLo_X4sfY.ar.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/29. One Dimension-kPlyl6JlLjY.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.en.vtt
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Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-I_v6ueT0k3M.pt-BR.vtt
717 Bytes
Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance--5--eKjgU7k.en-US.vtt
717 Bytes
Part 16-Module 02-Lesson 01_The Data Analysis Process/19. Exploring Data With Visuals-0i_9t4Wi0Og.en.vtt
717 Bytes
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.ar.vtt
717 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.ja.vtt
717 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.th.vtt
717 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/05. SD for Meal Price-PPcSvB1htPc.pt-BR.vtt
716 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic-wDjjmYJ9Z5Y.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.pt-BR.vtt
716 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.ja.vtt
716 Bytes
Part 16-Module 03-Lesson 03_SQL Aggregations/09. MIN MAX-1ewVsgWUih8.zh-CN.vtt
715 Bytes
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.en.vtt
715 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.en.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.pl.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.zh-CN.vtt
714 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/01. Social Networkers' Salaries-jNUbORceQPA.pt-BR.vtt
714 Bytes
Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance--5--eKjgU7k.en.vtt
714 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.en.vtt
714 Bytes
Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-dHS0BtLFTSQ.en.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/09. L4_Mini Project-CGPO68cOCgc.ar.vtt
713 Bytes
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-cUhgZ2BnWq0.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/36. Find Values-fUI1XABUTrY.pt-BR.vtt
712 Bytes
Part 13-Module 01-Lesson 02_D3 Building Blocks/25. NEW Create a Radius Scale-SUj-uKarNt0.zh-CN.vtt
712 Bytes
Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-KEdbHg_utV0.pt-BR.vtt
712 Bytes
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-8vi9b_LHHz8.pt-BR.vtt
712 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-P46v39eNSqM.zh-CN.vtt
712 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.it.vtt
712 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-7E7Czixpviw.es.vtt
711 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/18. Roll 5 Dice-GVoO-G6g3i0.pt-BR.vtt
711 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.pt-BR.vtt
711 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/13. Feature Scaling Mini-Project Video-e6zbTFctnJU.zh-CN.vtt
711 Bytes
Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.ar.vtt
711 Bytes
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-zAQygY7v2Ds.en.vtt
711 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-6yT3SlcmTl8.es.vtt
710 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.ja.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.es.vtt
709 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/29. Rent - Margin of Error-q413Zzil8lQ.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-udJvijJvs1M.en.vtt
709 Bytes
Part 13-Module 01-Lesson 01_Visualization Fundamentals/25. Transition to Tech Portion-WovqufP4nk0.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.es.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.es.vtt
708 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.zh-CN.vtt
708 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.ja.vtt
708 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.ja.vtt
708 Bytes
Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-l7P-e1M_qPA.ar.vtt
708 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.ja.vtt
708 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.zh-CN.vtt
708 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/11. Acne Medication-Xt2k2PWBwm4.zh-CN.vtt
707 Bytes
Part 08-Module 01-Lesson 01_Conduct a Job Search/04. Open Yourself Up to Opportunity-1OamTNkk1xM.es-MX.vtt
707 Bytes
Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.pt-BR.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.zh-CN.vtt
707 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.ar.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/12. Ratio of SDs-E14J3Thd0lc.pt-BR.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-ZwMY5rAAd7Q.pt-BR.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-PlFG87qPSB4.en.vtt
705 Bytes
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05-TyqZdKR8J_w.zh-CN.vtt
704 Bytes
Part 05-Module 02-Lesson 01_Data and Tables/06. Zoo-YG8zfeRXAvM.pt-BR.vtt
704 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.zh-CN.vtt
704 Bytes
Part 15-Module 01-Lesson 02_Design Principles/20. Onwards!-i-ulsdVHhCc.ar.vtt
704 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.en.vtt
704 Bytes
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.zh-CN.vtt
704 Bytes
Part 19-Module 01-Lesson 02_Design/22. Onwards!-i-ulsdVHhCc.ar.vtt
704 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.ar.vtt
703 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.zh-CN.vtt
703 Bytes
Part 18-Module 03-Lesson 01_Assessing Data/20. You Can Iterate-ZU8EnPbR-pk.zh-CN.vtt
703 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/21. Great Job!-fm66AGJzRI0.nl.vtt
702 Bytes
Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.en.vtt
702 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.it.vtt
702 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.pt-BR.vtt
702 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/05. DF - Add to 10-MxLG3eGzkI8.pt-BR.vtt
701 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.ja.vtt
701 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.zh-CN.vtt
701 Bytes
Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-rexAHoCGFMs.pt-BR.vtt
701 Bytes
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-PRjmvj6Vubs.zh-CN.vtt
701 Bytes
Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3-o7LnSu0CEb4.pt-BR.vtt
701 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-o_qyeIeRb_Y.pt-BR.vtt
701 Bytes
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Introduction to Percentiles-t7SX2ZEdxKA.zh-CN.vtt
701 Bytes
Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-VEXUQmVpazE.ar.vtt
700 Bytes
Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance--5--eKjgU7k.pt-BR.vtt
700 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.th.vtt
700 Bytes
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import Solution-QnTPEAGXJaE.pt-BR.vtt
700 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.zh-CN.vtt
699 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.zh-CN.vtt
699 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/01. Social Networkers' Salaries-jNUbORceQPA.en.vtt
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Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-W74CdB_pl5M.en.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.pt-BR.vtt
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Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ujpjeaxE6GU.zh-CN.vtt
698 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-q_zfkCwRg1w.zh-CN.vtt
698 Bytes
Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-BGNx2FiNFY0.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-BGNx2FiNFY0.pt-BR.vtt
698 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.zh-CN.vtt
698 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.pt-BR.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-KEdbHg_utV0.en.vtt
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Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.it.vtt
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/18. 26. Video Games-SyszPG1615c.es.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NTyY1HlXhiQ.zh-CN.vtt
696 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic-htd-vu8q3po.zh-CN.vtt
696 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.pt-BR.vtt
696 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-j2SP83afRS0.pt-BR.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.pt-BR.vtt
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/01. Introduction-wwzSxJvGwf0.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/16. Charts Types and Design Elements-h2tIZuzMuQU.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.it.vtt
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Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.pt-BR.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/01. Introduction-wwzSxJvGwf0.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/10. IQR-9dYN_oIly9I.pt-BR.vtt
694 Bytes
Part 05-Module 02-Lesson 01_Data and Tables/06. Zoo-YG8zfeRXAvM.zh-CN.vtt
694 Bytes
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-IC47yHGmgMk.zh-CN.vtt
694 Bytes
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.ar.vtt
694 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-lK2lDLdE6iA.zh-CN.vtt
693 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/28. Avg. Squared Dev. in Words-kgc_y-oJObM.en.vtt
693 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/06. DF - Marginal Totals-ykVKAjC9_TA.pt-BR.vtt
693 Bytes
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/14. Adding a DataFrame to a Series-IaM7ybOda8k.pt-BR.vtt
693 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/24. Changing the X-axis Interval-WwN3tYnOd8A.pt-BR.vtt
693 Bytes
Part 18-Module 03-Lesson 01_Assessing Data/20. You Can Iterate-ZU8EnPbR-pk.pt-BR.vtt
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review-xzZZZCZk5YM.ar.vtt
693 Bytes
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/14. Adding a DataFrame to a Series-IaM7ybOda8k.pt-BR.vtt
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/08. 24. Classical Music-3hSAWKrdO5s.zh-CN.vtt
692 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/20. Equation for Average Deviation-9jdZ9pfYP6A.pt-BR.vtt
692 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.zh-CN.vtt
692 Bytes
Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-z2R5CqjXrkA.en.vtt
692 Bytes
Part 12-Module 02-Lesson 01_Introduction and Efficiency/04. Syntax-08M93RaBSgU.zh-CN.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.pt-BR.vtt
692 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.pt-BR.vtt
692 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-hAPJsh81L98.pt-BR.vtt
691 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/02. Gambling in Vegas-qbcBbbm3lt8.pt-BR.vtt
691 Bytes
Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-5dt0N4XN-y4.pt-BR.vtt
691 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/06. Mark Z the Outlier-SADDVcUMQXM.en.vtt
690 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/28. Rent - Find CI-EZTRb9VBqAc.en.vtt
690 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.pt-BR.vtt
690 Bytes
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-8vi9b_LHHz8.en.vtt
690 Bytes
Part 13-Module 01-Lesson 07_Narrative Structures/22. Narratives Summary-QFXxRlLETyI.pt-BR.vtt
690 Bytes
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.hr.vtt
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Part 17-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.en.vtt
690 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-90OMETgfDyk.zh-CN.vtt
689 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-90OMETgfDyk.zh-CN.vtt
689 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/28. Klout Sampling Distribution (Mean)-8o5Elsb2pFY.pt-BR.vtt
689 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test-bD9ULWEsW0M.pt-BR.vtt
689 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.pt-BR.vtt
688 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.pt-BR.vtt
688 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/28. Probability of Obtaining Mean-00SWFc0sFIg.zh-CN.vtt
688 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/11. Bounds of Area-eADm6bXU3_0.en.vtt
688 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/20. Shoes - 95 CI-hN3Js3thgdY.zh-CN.vtt
688 Bytes
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-xYxD4GD1woo.zh-CN.vtt
688 Bytes
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.pt-BR.vtt
688 Bytes
Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-J2L_ZU-YMxc.en.vtt
688 Bytes
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-9DHPaCjg9HM.pt-BR.vtt
688 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.pt-BR.vtt
688 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/21. Great Job!-fm66AGJzRI0.en.vtt
687 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/12. Ratio of SDs-L4Jgcf9FNKA.en.vtt
687 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/13. SD of Sampling Distribution-rJ8NsbL5iTk.pt-BR.vtt
687 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.pt-BR.vtt
687 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Im9nOwm_fS8.es.vtt
686 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/11. What Is an Outlier-XP3F26GGuhE.pt-BR.vtt
686 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means-AocpFl2wt6k.zh-CN.vtt
686 Bytes
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/16. Subquery Conclusion-TUYvx2K9-5k.pt-BR.vtt
686 Bytes
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.es-ES.vtt
686 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-8LDZzqrCnS0.zh-CN.vtt
685 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/01. Intro to the PDF-QTVWqk09q1A.zh-CN.vtt
685 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-kjk--LHqtCw.ko.vtt
685 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.en.vtt
685 Bytes
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-f_SBhjbfmPw.ar.vtt
685 Bytes
Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.en.vtt
685 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.pt-BR.vtt
684 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.pt-BR.vtt
684 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-6yT3SlcmTl8.en.vtt
684 Bytes
Part 13-Module 01-Lesson 04_Design Principles/39. Junk Yard-2CT21UEcGQk.pt-BR.vtt
684 Bytes
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.ar.vtt
684 Bytes
Part 17-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.ar.vtt
684 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.ar.vtt
684 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-IJZs7KARtFo.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-IJZs7KARtFo.zh-CN.vtt
683 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-7E7Czixpviw.pt-BR.vtt
683 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/11. Two-Tailed Test-4fWHT1f72B8.zh-CN.vtt
683 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/32. Compute CI-nCg6F5QQZsI.zh-CN.vtt
683 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.zh-CN.vtt
683 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.pt-BR.vtt
683 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-611qWzIxGmU.ar.vtt
683 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-611qWzIxGmU.ar.vtt
683 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-VdVjOC6UP6c.zh-CN.vtt
682 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/07. Chop Off the Tails-NmlhFjNHmXc.zh-CN.vtt
682 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/10. Calculate SDs-x-VMDl-3p7M.zh-CN.vtt
682 Bytes
Part 05-Module 02-Lesson 01_Data and Tables/06. Zoo-YG8zfeRXAvM.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/17. Summary-1Gp4l-ZTCVk.en.vtt
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Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-wJV1cRjmIYY.ar.vtt
682 Bytes
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 2-so5zydnbYEg.en.vtt
682 Bytes
Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.en.vtt
682 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.es-ES.vtt
682 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.en.vtt
682 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-TE2BZql64XY.es.vtt
681 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-y_Hp6nNKxdM.zh-CN.vtt
681 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.es-ES.vtt
681 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Im9nOwm_fS8.en.vtt
680 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/20. Standard Error When n Increases-dU3LgB8i6XM.en.vtt
680 Bytes
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-lS5DfbsWH34.zh-CN.vtt
680 Bytes
Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-OVoEIInUg9A.en.vtt
680 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.pt-BR.vtt
680 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/03. Tetrahedral Die-l7p3uldaCks.pt-BR.vtt
679 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic-wDjjmYJ9Z5Y.en.vtt
679 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.en.vtt
679 Bytes
Part 13-Module 01-Lesson 01_Visualization Fundamentals/25. Transition to Tech Portion-WovqufP4nk0.en.vtt
679 Bytes
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-ta5Nz-YCn6g.en.vtt
679 Bytes
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.ar.vtt
679 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.es-ES.vtt
679 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.es-ES.vtt
679 Bytes
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/18. 26. Video Games-SyszPG1615c.pt-BR.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/19. Lessons Completed in First Week -kL0HS6KWRcw.pt-BR.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages-_0AHmKkfjTo.ar.vtt
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Part 09-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.pt-BR.vtt
678 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/24. Changing the X-axis Interval-WwN3tYnOd8A.en.vtt
678 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-t0yIetl9ZxI.zh-CN.vtt
677 Bytes
Part 09-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.en.vtt
677 Bytes
Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-c1gvsNx_ypg.zh-CN.vtt
677 Bytes
Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-R0RqC-yerD4.ar.vtt
677 Bytes
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.zh-CN.vtt
677 Bytes
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.th.vtt
677 Bytes
Part 18-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python -cUmcLjWgxwM.pt-BR.vtt
677 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-nRurXCTYxG4.en.vtt
676 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/21. Standard Normal Distribution-5B-vrhyedws.zh-CN.vtt
676 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/21. Great Job!-fm66AGJzRI0.zh-CN.vtt
676 Bytes
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.zh-CN.vtt
676 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/12. Define Outlier-jxatUS0YvtU.pt-BR.vtt
675 Bytes
Part 08-Module 01-Lesson 01_Conduct a Job Search/04. Open Yourself Up to Opportunity-1OamTNkk1xM.zh-CN.vtt
675 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.en.vtt
675 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-Lb_v4vj3TNs.ar.vtt
675 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.en.vtt
675 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.zh-CN.vtt
675 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-Lb_v4vj3TNs.ar.vtt
675 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.zh-CN.vtt
674 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.zh-CN.vtt
674 Bytes
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-P1NzBPnfl2E.en.vtt
674 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/10. IQR-9dYN_oIly9I.zh-CN.vtt
673 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above-lGHZ4w8UqIk.zh-CN.vtt
673 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error-w-7MoreKqaU.en.vtt
673 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-mdCk7Gwkd4g.pt-BR.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results-tmAlVZCbgFA.ar.vtt
673 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.pt-BR.vtt
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Part 21-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.ar.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Im9nOwm_fS8.zh-CN.vtt
672 Bytes
Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-udJvijJvs1M.zh-CN.vtt
672 Bytes
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-xSQTzAeeoEc.pt-BR.vtt
672 Bytes
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-9DHPaCjg9HM.en.vtt
672 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/36. Find Values-fUI1XABUTrY.en.vtt
671 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/10. Report CI Results 2-eVTzjsolEwI.zh-CN.vtt
671 Bytes
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-wJV1cRjmIYY.pt-BR.vtt
671 Bytes
Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-KEdbHg_utV0.zh-CN.vtt
671 Bytes
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-ta5Nz-YCn6g.pt-BR.vtt
671 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.es-ES.vtt
671 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.it.vtt
671 Bytes
Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.es-ES.vtt
671 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.ar.vtt
670 Bytes
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.zh-CN.vtt
670 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/07. More Detail-E931DQC0hno.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.ar.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.ar.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-_itWo-gUTzY.ar.vtt
669 Bytes
Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.ja.vtt
669 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-mdCk7Gwkd4g.en.vtt
668 Bytes
Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-rexAHoCGFMs.en.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-dxw2VFq5sAc.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-F7PIJM0q524.en.vtt
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Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-I_v6ueT0k3M.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-NNE8Cr77ytg.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-NNE8Cr77ytg.zh-CN.vtt
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Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-xSQTzAeeoEc.en.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-mpYpT6nZVEo.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.ar.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.es-ES.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.ar.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-7E7Czixpviw.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/12. Using the Z-Table-EeT7osOfzJE.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.zh-CN.vtt
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Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3-o7LnSu0CEb4.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD-UbnrfnB8vcs.zh-CN.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings--laXTx9corQ.ar.vtt
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Part 08-Module 01-Lesson 01_Conduct a Job Search/04. Open Yourself Up to Opportunity-1OamTNkk1xM.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/34. Updated World Cup Data Set-tA_je-rSL7c.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-T5TBKcjzleI.es.vtt
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Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-0PFq8zoaNWU.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.ar.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.hr.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-0PFq8zoaNWU.ar.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.ar.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/30. Conclusion-33thdy0IjPE.en.vtt
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Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-W74CdB_pl5M.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.ja.vtt
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Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 -aEGtqoWIJIc.zh-CN.vtt
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Part 05-Module 01-Lesson 05_Data Quality/20. Conclusion-fSwaNltHTio.ar.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-3FO2y4tlZ3A.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-F7PIJM0q524.pt-BR.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-Xrl2Hd--NWs.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-HFCs3LbQ5Z0.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-5cs9badCyPQ.ar.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download Solution-SDqdLhgsBNc.zh-CN.vtt
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Part 18-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python -cUmcLjWgxwM.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test-zqj1NZbe5os.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores-8XZqX03Y6Vk.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.en.vtt
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Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-WDADret_QqE.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-j2SP83afRS0.en.vtt
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Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.zh-CN.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.en.vtt
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/12. Congratulations!-sCQ7ZViODaw.en.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/30. Conclusion-33thdy0IjPE.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.th.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.ja.vtt
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/09. 25. Caffeine--D3nyKUK1kY.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD-1SL8FGhaKqA.zh-CN.vtt
656 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-Och80L_uNjU.zh-CN.vtt
656 Bytes
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.zh-CN.vtt
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/21. Conclusion-UFwgr6tLcuI.en.vtt
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Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.es-ES.vtt
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Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.it.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.ar.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-ydpbvqLmLQI.zh-CN.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values-kNsdYqgn9Mk.en.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.ja.vtt
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Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-Fi3uuGj8bhs.zh-CN.vtt
655 Bytes
Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.pt-BR.vtt
655 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction-FGbxq1hQgtk.en.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes-icmKCnOXQdI.zh-CN.vtt
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Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance--5--eKjgU7k.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.th.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.ar.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-TE2BZql64XY.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/15. SD of Karma Points per Post-gIR0M2Jxb0k.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.ja.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.pt-BR.vtt
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Measures of Center - The Mode-NE81NZgECqg.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.th.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/18. Finches - Find t-Statistic-eAN4NfHSgk8.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.ar.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-a2GCyz_N0oY.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/02. Accuracy Review-g3sxDtlGlAM.pt-BR.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-o_qyeIeRb_Y.zh-CN.vtt
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Part 21-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.ar.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-a1sLkQtfUKc.pt-BR.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/05. Critical Values 0.001-AdLGLYYYVao.zh-CN.vtt
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Part 04-Module 02-Lesson 01_Data Analysis Process/19. Lessons Completed in First Week -kL0HS6KWRcw.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/33. Highlight Countries-wjUenfTcSG0.zh-CN.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.en.vtt
650 Bytes
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.ar.vtt
650 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.ar.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-a1sLkQtfUKc.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/18. Roll 5 Dice-GVoO-G6g3i0.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/30. Sampling Distribution Shape-FJjI93XvC50.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/29. Rent - Margin of Error-q413Zzil8lQ.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-dHS0BtLFTSQ.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.zh-CN.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!-UjaFiRdHPZg.zh-CN.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/09. Report CI Results-pr-2ZaCDzPY.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.ja.vtt
647 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/14. Two-Tailed Critical Values 0.001-KD_AqWVG4Cc.pt-BR.vtt
646 Bytes
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/14. Adding a DataFrame to a Series-IaM7ybOda8k.en.vtt
646 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-gydx9-h1liU.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.ja.vtt
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Part 13-Module 01-Lesson 04_Design Principles/16. Charts Types and Design Elements-h2tIZuzMuQU.en.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-HH73nOnzRrc.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.en.vtt
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/14. Adding a DataFrame to a Series-IaM7ybOda8k.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less-wDRJK3htUZE.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/28. Klout Sampling Distribution (Mean)-8o5Elsb2pFY.en.vtt
645 Bytes
Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-W74CdB_pl5M.zh-CN.vtt
645 Bytes
Part 21-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.en.vtt
645 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/02. Mean of Treated Population-ecy3VY8eNGM.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic-0iKPoKeApJI.zh-CN.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision-tSZJDW3qp_I.zh-CN.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.ja.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.ar.vtt
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Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.en.vtt
644 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.zh-CN.vtt
644 Bytes
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download-a5o3ck1bxEs.zh-CN.vtt
644 Bytes
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review-xzZZZCZk5YM.pt-BR.vtt
644 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/17. Finches - Mean and s-XhVy8ALgO0U.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-BbJfVyCm21o.pt-BR.vtt
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 2-so5zydnbYEg.zh-CN.vtt
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Part 17-Module 01-Lesson 14_Regression/01. Regression Introduction-PKqSS0TzXeA.zh-CN.vtt
643 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test-bD9ULWEsW0M.zh-CN.vtt
642 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/05. SD for Meal Price-PPcSvB1htPc.zh-CN.vtt
642 Bytes
Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-HH73nOnzRrc.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.pt-BR.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/39. Junk Yard-2CT21UEcGQk.en.vtt
641 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-o_qyeIeRb_Y.en.vtt
641 Bytes
Part 18-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python -cUmcLjWgxwM.zh-CN.vtt
641 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-NcWS_BvM3IU.pt-BR.vtt
640 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error-w-7MoreKqaU.zh-CN.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-q23Nlo1Rfn4.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/22. Narratives Summary-QFXxRlLETyI.en.vtt
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Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.hr.vtt
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Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.ar.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/29. One Dimension-kPlyl6JlLjY.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-PYNWtLgtRfU.pt-BR.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-3FO2y4tlZ3A.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-kjk--LHqtCw.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-a2GCyz_N0oY.ja.vtt
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Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.hr.vtt
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/12. Congratulations!-sCQ7ZViODaw.pt-BR.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/17. Check You Out-tgni8KzxWzA.ar.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare-B2KnUg5iz0Y.pt-BR.vtt
636 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/02. Accuracy Review-g3sxDtlGlAM.en.vtt
636 Bytes
Part 16-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data-AJF5smH1TJU.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/17. Summary-1Gp4l-ZTCVk.zh-CN.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-9AVeGkUcPYQ.ar.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-bRhdim9PTFI.en.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-v2_aFAmQxfw.ar.vtt
635 Bytes
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.en.vtt
635 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-3R0LfaKa-fw.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/28. Rent - Find CI-1bXAy-6Pxf0.en.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-ZwMY5rAAd7Q.en.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.th.vtt
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import Solution-QnTPEAGXJaE.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-T5TBKcjzleI.en.vtt
633 Bytes
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-CZnFt1rOfwc.en.vtt
633 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.zh-CN.vtt
633 Bytes
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-xSQTzAeeoEc.zh-CN.vtt
633 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.zh-CN.vtt
633 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.en.vtt
633 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/28. Avg. Squared Dev. in Words-kgc_y-oJObM.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.ja.vtt
632 Bytes
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.ja.vtt
632 Bytes
Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.en-US.vtt
632 Bytes
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-5v1jxDIwGqk.ar.vtt
632 Bytes
Part 16-Module 02-Lesson 01_The Data Analysis Process/19. Exploring Data With Visuals-0i_9t4Wi0Og.zh-CN.vtt
632 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.ar.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-nRurXCTYxG4.zh-CN.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/18. Conclusion-P7H8wjCIJ6k.ar.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.zh-CN.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-bRhdim9PTFI.pt-BR.vtt
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Part 16-Module 03-Lesson 05_SQL Data Cleaning/08. CONCAT-bCxZnQN28Y4.en.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/19. Conclusion-P7H8wjCIJ6k.ar.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/05. DF - Add to 10-MxLG3eGzkI8.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/18. Finches - Find t-Statistic-eAN4NfHSgk8.en.vtt
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Part 06-Module 01-Lesson 01_Working with MongoDB/30. Conclusion-mjPfjzOWiDw.ar.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.pt-BR.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/34. Updated World Cup Data Set-tA_je-rSL7c.en.vtt
629 Bytes
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Measures of Center - The Mode-NE81NZgECqg.pt-BR.vtt
629 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.zh-CN.vtt
629 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.es-ES.vtt
629 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/09. Report CI Results-pr-2ZaCDzPY.zh-CN.vtt
628 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM-4FAowd-l1p4.pt-BR.vtt
628 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.pt-BR.vtt
628 Bytes
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.ja.vtt
628 Bytes
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-Njbmexuo7fo.pt-BR.vtt
628 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.en.vtt
628 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR-o2n0nea_1T0.en.vtt
627 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5-HbS35vDe_x0.zh-CN.vtt
627 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/02. Gambling in Vegas-qbcBbbm3lt8.en.vtt
627 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/12. Ratio of SDs-L4Jgcf9FNKA.zh-CN.vtt
627 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/11. Bounds of Area-UPRiS4xRnow.zh-CN.vtt
627 Bytes
Part 09-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.zh-CN.vtt
627 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6--LtbhZvwwM8.pt-BR.vtt
627 Bytes
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-AI9kNE00Los.zh-CN.vtt
627 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.ja.vtt
627 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/02. Should You Get an Account-pZ_GUg7z548.en.vtt
626 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/13. SD of Sampling Distribution-rJ8NsbL5iTk.en.vtt
626 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/30. Sampling Distribution Shape-FJjI93XvC50.pt-BR.vtt
626 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means-kuTOS0wZJd4.pt-BR.vtt
626 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.zh-CN.vtt
626 Bytes
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-cUhgZ2BnWq0.pt-BR.vtt
626 Bytes
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-PYNWtLgtRfU.en.vtt
626 Bytes
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-7ZvLztG6xhg.ar.vtt
626 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.ar.vtt
626 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/06. Mark Z the Outlier-SADDVcUMQXM.zh-CN.vtt
625 Bytes
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-eVAEO2QRdM0.pt-BR.vtt
625 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.ja.vtt
625 Bytes
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.it.vtt
625 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-6yT3SlcmTl8.zh-CN.vtt
624 Bytes
Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ZlDdxWYv6jw.ar.vtt
624 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.ar.vtt
624 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.zh-CN.vtt
623 Bytes
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-Njbmexuo7fo.en.vtt
623 Bytes
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.ja.vtt
623 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.ar.vtt
623 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI-fFY4isvV-Sk.zh-CN.vtt
622 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-X_5v9jxuLrQ.ar.vtt
622 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.ar.vtt
622 Bytes
Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-5dt0N4XN-y4.zh-CN.vtt
622 Bytes
Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.en.vtt
622 Bytes
Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-4EpW5acw55c.ar.vtt
622 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.en.vtt
622 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.zh-CN.vtt
622 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions-szqkEhERjDI.es.vtt
621 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.ja.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.en.vtt
620 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-NNE8Cr77ytg.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.en.vtt
620 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-NNE8Cr77ytg.es.vtt
620 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-dSgIDN1gz5k.pt-BR.vtt
620 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-8SqL0v_FSsc.ar.vtt
620 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.ja.vtt
620 Bytes
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/21. Conclusion-UFwgr6tLcuI.zh-CN.vtt
620 Bytes
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/19. Congratulations!-_FPpbuuW-1o.pt-BR.vtt
620 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.pt-BR.vtt
620 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-NNE8Cr77ytg.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-NNE8Cr77ytg.en.vtt
619 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic-y1QSAIUlupg.en.vtt
619 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.en.vtt
619 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.pt-BR.vtt
618 Bytes
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.it.vtt
618 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.ja.vtt
618 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.pt-BR.vtt
618 Bytes
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/12. Congratulations!-sCQ7ZViODaw.zh-CN.vtt
618 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.en-US.vtt
617 Bytes
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/15. Conclusion-PXBdIBgFTL4.ar.vtt
617 Bytes
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.ja.vtt
617 Bytes
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.ru.vtt
617 Bytes
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.en.vtt
617 Bytes
Part 17-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.zh-CN.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/01. Hypothesis Testing Introduction-Qi6F2rJAmrA.en.vtt
617 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.en-US.vtt
617 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/13. SD of Sampling Distribution-tPVKll2xFUw.zh-CN.vtt
616 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/13. Two-Tailed Critical Values 0.01-Fzich-V7ZO0.zh-CN.vtt
616 Bytes
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-CZnFt1rOfwc.pt-BR.vtt
616 Bytes
Part 13-Module 01-Lesson 04_Design Principles/44. Leland Wilkinson-w7TLo_X4sfY.pt-BR.vtt
616 Bytes
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/01. Communicating with your data-KDnca1zszIo.ar.vtt
616 Bytes
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.zh-CN.vtt
616 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.zh-CN.vtt
616 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.zh-CN.vtt
616 Bytes
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/01. Communicating With Your Data-KDnca1zszIo.ar.vtt
616 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs-PXHHbaYnciY.zh-CN.vtt
615 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI-guhmjr4BqSo.pt-BR.vtt
615 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.ar.vtt
615 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region-SyNQ2mElRi0.pt-BR.vtt
614 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.ja.vtt
614 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/02. Should You Get an Account-pZ_GUg7z548.pt-BR.vtt
613 Bytes
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-wJV1cRjmIYY.en.vtt
613 Bytes
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-Xrl2Hd--NWs.en.vtt
613 Bytes
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-zAQygY7v2Ds.zh-CN.vtt
613 Bytes
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Measures of Center - The Mode-NE81NZgECqg.zh-CN.vtt
613 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/07. More Detail-E931DQC0hno.zh-CN.vtt
612 Bytes
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/01. Communicating with your data-KDnca1zszIo.pt-BR.vtt
612 Bytes
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/01. Communicating With Your Data-KDnca1zszIo.pt-BR.vtt
612 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-a1sLkQtfUKc.zh-CN.vtt
611 Bytes
Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-kIITzFRh5mQ.pt-BR.vtt
611 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.zh-CN.vtt
611 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.en.vtt
611 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.ja.vtt
611 Bytes
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.es-ES.vtt
611 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.en.vtt
610 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.en.vtt
610 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-mdCk7Gwkd4g.zh-CN.vtt
610 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.en.vtt
610 Bytes
Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-OVoEIInUg9A.zh-CN.vtt
610 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.en.vtt
610 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes-FxF9WyIPFbo.zh-CN.vtt
609 Bytes
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/13. Series Indexes-FA4mkuoDoJI.ar.vtt
609 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6--LtbhZvwwM8.en.vtt
609 Bytes
Part 13-Module 01-Lesson 04_Design Principles/32. Do No Harm-BIQPOMfDXjs.ar.vtt
609 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.zh-CN.vtt
609 Bytes
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/14. Series Indexes-FA4mkuoDoJI.ar.vtt
609 Bytes
Part 01-Module 01-Lesson 01_Nanodegree Orientation/02. Introduction-fxNSn63xFvA.pt-BR.vtt
608 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.zh-CN.vtt
608 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.zh-CN.vtt
608 Bytes
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/18. 26. Video Games-SyszPG1615c.en.vtt
608 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/07. Sampling Distribution-kQevFvu_dL0.pt-BR.vtt
608 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2-It6AEuSDQw0.ar.vtt
608 Bytes
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-TpVxnYcI_uw.pt-BR.vtt
608 Bytes
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-8vi9b_LHHz8.zh-CN.vtt
608 Bytes
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.es-ES.vtt
608 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.ja.vtt
608 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.ar.vtt
607 Bytes
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-Ee2o-0arldg.zh-CN.vtt
606 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/01. Social Networkers' Salaries-jNUbORceQPA.zh-CN.vtt
606 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-AM-d6qA5nnI.hi.vtt
606 Bytes
Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.pt-BR.vtt
606 Bytes
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import Solution-QnTPEAGXJaE.zh-CN.vtt
606 Bytes
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-TpVxnYcI_uw.en.vtt
605 Bytes
Part 13-Module 01-Lesson 02_D3 Building Blocks/16. -6-NsyLPx738.en-US.vtt
605 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/18. Roll 5 Dice-GVoO-G6g3i0.zh-CN.vtt
604 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.ar.vtt
604 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.th.vtt
604 Bytes
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.th.vtt
603 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-dxw2VFq5sAc.es.vtt
602 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR-o2n0nea_1T0.zh-CN.vtt
602 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/32. Location of Mean on Distribution-k3RUgrtFIl4.zh-CN.vtt
602 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.ar.vtt
602 Bytes
Part 13-Module 01-Lesson 02_D3 Building Blocks/16. -6-NsyLPx738.en.vtt
602 Bytes
Part 16-Module 03-Lesson 05_SQL Data Cleaning/17. Data Cleaning Conclusion-KkHqnvD9BWY.pt-BR.vtt
602 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-xE00wGLivN4.pt-BR.vtt
601 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/29. One Dimension-kPlyl6JlLjY.zh-CN.vtt
601 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/28. Klout Sampling Distribution (Mean)-8o5Elsb2pFY.zh-CN.vtt
601 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-gydx9-h1liU.en.vtt
601 Bytes
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-Kn9v0KGDsvc.pt-BR.vtt
601 Bytes
Part 11-Module 01-Lesson 09_Clustering/13. Some challenges of k-means-e2CdlG5P4WA.en.vtt
601 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/25. Bar Chart Issues-MNsMZH1Y0Js.ar.vtt
601 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-9JHRpVTMuK4.zh-Hans.vtt
600 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.zh-CN.vtt
600 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.pt-BR.vtt
600 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.en.vtt
600 Bytes
Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-kIITzFRh5mQ.en.vtt
599 Bytes
Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-20QVVrTcp2A.pt-BR.vtt
599 Bytes
Part 13-Module 01-Lesson 04_Design Principles/16. Charts Types and Design Elements-h2tIZuzMuQU.zh-CN.vtt
599 Bytes
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.hr.vtt
599 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.pt-BR.vtt
599 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.ar.vtt
599 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.en.vtt
599 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.en.vtt
598 Bytes
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.it.vtt
598 Bytes
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.pt-BR.vtt
598 Bytes
Part 17-Module 01-Lesson 13_Case Study AB tests/01. Case Study Introduction-J5uvdPxHIfs.en.vtt
598 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.ar.vtt
597 Bytes
Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.ar.vtt
597 Bytes
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.ja.vtt
597 Bytes
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.pt-BR.vtt
597 Bytes
Part 04-Module 02-Lesson 01_Data Analysis Process/19. Lessons Completed in First Week -kL0HS6KWRcw.zh-CN.vtt
596 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-gydx9-h1liU.zh-CN.vtt
596 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.en.vtt
596 Bytes
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-0ZBp8oWySAc.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-BbJfVyCm21o.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-BbJfVyCm21o.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.ja.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.es.vtt
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/03. Assessing the Quality of Data Pt. 1-Dezhyk312lQ.ar.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-e_8DmUBHAao.ar.vtt
595 Bytes
Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.en.vtt
595 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.es-ES.vtt
595 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-3R0LfaKa-fw.es.vtt
594 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.ja.vtt
594 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.zh-CN.vtt
594 Bytes
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.ja.vtt
594 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20-W0R3XOK1IfE.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.zh-CN.vtt
593 Bytes
Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3-o7LnSu0CEb4.zh-CN.vtt
593 Bytes
Part 13-Module 01-Lesson 02_D3 Building Blocks/14. -E-Bd6EEl20s.en-US.vtt
593 Bytes
Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-l7P-e1M_qPA.pt-BR.vtt
593 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-783QmxtIx58.zh-CN.vtt
593 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.pt-BR.vtt
593 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/02. Probability-Wf7m7ygRvz8.pt-BR.vtt
592 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size-VXH1be4d1Nc.pt-BR.vtt
592 Bytes
Part 09-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.ja.vtt
592 Bytes
Part 13-Module 01-Lesson 04_Design Principles/44. Leland Wilkinson-w7TLo_X4sfY.en.vtt
592 Bytes
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare-B2KnUg5iz0Y.en.vtt
591 Bytes
Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-VEXUQmVpazE.pt-BR.vtt
591 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.ar.vtt
591 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.en.vtt
591 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.zh-CN.vtt
590 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.zh-CN.vtt
590 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-ypEVJhggHQc.pt-BR.vtt
590 Bytes
Part 13-Module 01-Lesson 02_D3 Building Blocks/14. -E-Bd6EEl20s.en.vtt
590 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-HFCs3LbQ5Z0.en.vtt
590 Bytes
Part 01-Module 01-Lesson 01_Nanodegree Orientation/02. Introduction-fxNSn63xFvA.en.vtt
589 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-Khxyqd5vtOo.pt-BR.vtt
589 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/20. Standard Error When n Increases-dU3LgB8i6XM.zh-CN.vtt
589 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/28. Rent - Find CI-EZTRb9VBqAc.zh-CN.vtt
589 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.pt-BR.vtt
589 Bytes
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-3FO2y4tlZ3A.zh-CN.vtt
589 Bytes
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-wJV1cRjmIYY.zh-CN.vtt
589 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.pt-BR.vtt
589 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.ja.vtt
589 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/20. Equation for Average Deviation-9jdZ9pfYP6A.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size-tX7p7HXlKBQ.pt-BR.vtt
588 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-mdCk7Gwkd4g.ja.vtt
588 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.ar.vtt
588 Bytes
Part 13-Module 01-Lesson 01_Visualization Fundamentals/25. Transition to Tech Portion-WovqufP4nk0.zh-CN.vtt
588 Bytes
Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-l7P-e1M_qPA.en.vtt
588 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/24. Changing the X-axis Interval-WwN3tYnOd8A.zh-CN.vtt
588 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.en.vtt
587 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.zh-CN.vtt
587 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-5cs9badCyPQ.pt-BR.vtt
587 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.ja.vtt
587 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/36. Find Values-fUI1XABUTrY.zh-CN.vtt
586 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/20. Alternative Hypothesis-EH59aCNpHS8.zh-CN.vtt
586 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/29. Congrats-psVUIDdsbA0.pt-BR.vtt
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Part 17-Module 01-Lesson 13_Case Study AB tests/18. Conclusion-qmGjRpMVBz8.en.vtt
586 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/07. Sampling Distribution-kQevFvu_dL0.en.vtt
585 Bytes
Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-VEXUQmVpazE.en.vtt
585 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-5cs9badCyPQ.en.vtt
585 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-2yo4xrFnDyg.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-Khxyqd5vtOo.en.vtt
584 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-hAPJsh81L98.en-US.vtt
584 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/08. Probability Mean or = 3-JSlSjQwhIAI.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.zh-CN.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-J2L_ZU-YMxc.zh-CN.vtt
584 Bytes
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-eVAEO2QRdM0.en.vtt
584 Bytes
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/23. L3 outro-y46uDftUXHo.pt-BR.vtt
584 Bytes
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.ja.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.ar.vtt
584 Bytes
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/47. What's Next-y46uDftUXHo.pt-BR.vtt
584 Bytes
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-P1NzBPnfl2E.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.ar.vtt
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Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-ZMfwPUrOFsE.ar.vtt
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Part 21-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.pt-BR.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings--laXTx9corQ.en.vtt
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Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings--laXTx9corQ.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-gydx9-h1liU.ja.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.zh-CN.vtt
582 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-FwaYsmnlLM4.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.zh-CN.vtt
582 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.zh-CN.vtt
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Part 17-Module 01-Lesson 12_Hypothesis Testing/01. Hypothesis Testing Introduction-Qi6F2rJAmrA.pt-BR.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-FwaYsmnlLM4.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/09. Operational Definition-khRQslIcqyY.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/09. Operational Definition-khRQslIcqyY.pt-BR.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/04. Relative Frequency Histogram-1K7_1uPm8F8.pt-BR.vtt
581 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/37. Keyboards - Decision-PXDcczTlqLc.en.vtt
581 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.en.vtt
581 Bytes
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/21. Visualization design -TTGYKv5Qta0.pt-BR.vtt
581 Bytes
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/08. Further Learning-SnLQlP5J7c8.pt-BR.vtt
581 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-hAPJsh81L98.en.vtt
580 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/02. Mean of Treated Population-ecy3VY8eNGM.zh-CN.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision-k1plVVNoyeY.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.zh-CN.vtt
580 Bytes
Part 13-Module 01-Lesson 04_Design Principles/39. Junk Yard-2CT21UEcGQk.zh-CN.vtt
580 Bytes
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/09. 25. Caffeine--D3nyKUK1kY.es.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-u4rfZfA2ANk.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-Khxyqd5vtOo.es.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-7E7Czixpviw.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-T5TBKcjzleI.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-5tdFjuAX9u0.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.zh-CN.vtt
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Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.en.vtt
579 Bytes
Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-I_v6ueT0k3M.zh-CN.vtt
579 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/27. The Update Function-z5f-oK0jwZk.zh-CN.vtt
579 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.zh-Hans.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.th.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/12. Define Outlier-jxatUS0YvtU.en.vtt
578 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/12. Ratio of SDs-E14J3Thd0lc.en.vtt
578 Bytes
Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-q23Nlo1Rfn4.en.vtt
578 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.ja.vtt
578 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6--LtbhZvwwM8.zh-CN.vtt
578 Bytes
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-9DHPaCjg9HM.zh-CN.vtt
578 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.th.vtt
578 Bytes
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.pt-BR.vtt
577 Bytes
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.zh-CN.vtt
577 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-a2GCyz_N0oY.pt-BR.vtt
576 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/33. Congrats-Qy8VYdqoxGA.pt-BR.vtt
576 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/03. Tetrahedral Die-WtGcIl_o_40.pt-BR.vtt
575 Bytes
Part 04-Module 02-Lesson 01_Data Analysis Process/30. Conclusion-33thdy0IjPE.zh-CN.vtt
575 Bytes
Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-z2R5CqjXrkA.zh-CN.vtt
575 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-n7gp8USw0Jw.en.vtt
575 Bytes
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.hr.vtt
575 Bytes
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.es-ES.vtt
575 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.en.vtt
575 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/10. Two-Tailed t-Test-zlHtHBeJhww.zh-CN.vtt
574 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-a2GCyz_N0oY.en-US.vtt
574 Bytes
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/14. Adding a DataFrame to a Series-IaM7ybOda8k.zh-CN.vtt
573 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.ja.vtt
573 Bytes
Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-20QVVrTcp2A.en.vtt
573 Bytes
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.pt-BR.vtt
573 Bytes
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/14. Adding a DataFrame to a Series-IaM7ybOda8k.zh-CN.vtt
573 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-NcWS_BvM3IU.es.vtt
572 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/06. DF - Marginal Totals-ykVKAjC9_TA.en.vtt
572 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/29. Congrats-psVUIDdsbA0.en.vtt
572 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.ja.vtt
572 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.zh-CN.vtt
572 Bytes
Part 17-Module 01-Lesson 13_Case Study AB tests/14. Analyzing Multiple Metrics-DtZghKNa7Ak.en.vtt
572 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-NNE8Cr77ytg.pt-BR.vtt
571 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-NNE8Cr77ytg.pt-BR.vtt
571 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic-y1QSAIUlupg.zh-CN.vtt
571 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.pt-BR.vtt
571 Bytes
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.it.vtt
571 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.en.vtt
571 Bytes
Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-F7PIJM0q524.zh-CN.vtt
570 Bytes
Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.ar.vtt
570 Bytes
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.pt-BR.vtt
570 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-9JHRpVTMuK4.zh-CN.vtt
569 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/37. Keyboards - Decision-PXDcczTlqLc.pt-BR.vtt
569 Bytes
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.en-US.vtt
569 Bytes
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.en.vtt
569 Bytes
Part 21-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.zh-CN.vtt
569 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-kjk--LHqtCw.zh-CN.vtt
568 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/05. DF - Add to 10-MxLG3eGzkI8.zh-CN.vtt
568 Bytes
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.pt-BR.vtt
568 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.pt-BR.vtt
568 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/28. Rent - Find CI-1bXAy-6Pxf0.zh-CN.vtt
567 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-611qWzIxGmU.pt-BR.vtt
567 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction-FGbxq1hQgtk.pt-BR.vtt
567 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-611qWzIxGmU.pt-BR.vtt
567 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-VLgrNOLomc0.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-VLgrNOLomc0.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.en.vtt
566 Bytes
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-O5B-Z5SUoc8.en.vtt
566 Bytes
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/23. L3 outro-y46uDftUXHo.ar.vtt
566 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction-FGbxq1hQgtk.zh-CN.vtt
566 Bytes
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.es-ES.vtt
566 Bytes
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/47. What's Next-y46uDftUXHo.ar.vtt
566 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/30. r^2-mnfgAsAVaTQ.zh-CN.vtt
565 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-a2GCyz_N0oY.en.vtt
565 Bytes
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.hr.vtt
565 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.es-ES.vtt
565 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.es.vtt
564 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.es.vtt
564 Bytes
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-ta5Nz-YCn6g.zh-CN.vtt
564 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/33. Congrats-Qy8VYdqoxGA.en.vtt
564 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-NcWS_BvM3IU.en.vtt
563 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.zh-CN.vtt
563 Bytes
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.ar.vtt
563 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-n7gp8USw0Jw.pt-BR.vtt
563 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.pt-BR.vtt
563 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-5tdFjuAX9u0.es.vtt
562 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI-guhmjr4BqSo.en.vtt
562 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.zh-CN.vtt
562 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.ar.vtt
562 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/30. Sampling Distribution Shape-FJjI93XvC50.zh-CN.vtt
561 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/01. t-Distribution-TC2Ro6pFAqA.pt-BR.vtt
561 Bytes
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-Kn9v0KGDsvc.en.vtt
561 Bytes
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-O5B-Z5SUoc8.pt-BR.vtt
561 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.ar.vtt
561 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1-tYaQItpvXUo.en.vtt
560 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.pt-BR.vtt
560 Bytes
Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.zh-CN.vtt
560 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.es-ES.vtt
560 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less-wDRJK3htUZE.en.vtt
559 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size-kKT56up4n_o.pt-BR.vtt
559 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-jJSkp9n3kA8.pt-BR.vtt
559 Bytes
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.ar.vtt
559 Bytes
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/09. 25. Caffeine--D3nyKUK1kY.en.vtt
558 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-xE00wGLivN4.es.vtt
558 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-TE2BZql64XY.zh-CN.vtt
558 Bytes
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.zh-CN.vtt
558 Bytes
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.en.vtt
558 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.ar.vtt
558 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores-8XZqX03Y6Vk.zh-CN.vtt
557 Bytes
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-CZnFt1rOfwc.zh-CN.vtt
557 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.ja.vtt
557 Bytes
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/18. Conclusion-P7H8wjCIJ6k.pt-BR.vtt
556 Bytes
Part 05-Module 01-Lesson 03_Data in More Complex Formats/01. Welcome to Lesson 2-53b_nnGcnBY.ar.vtt
556 Bytes
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-bnwLadF8gKo.pt-BR.vtt
556 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-ZwMY5rAAd7Q.zh-CN.vtt
556 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.zh-CN.vtt
556 Bytes
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/19. Conclusion-P7H8wjCIJ6k.pt-BR.vtt
556 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/02. Should You Get an Account-pZ_GUg7z548.zh-CN.vtt
555 Bytes
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Window Functions Conclusion-2ZdocDMw7D8.en.vtt
555 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.zh-CN.vtt
554 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.th.vtt
554 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1-tYaQItpvXUo.pt-BR.vtt
553 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score--Sw8Dlo0fx4.pt-BR.vtt
553 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value-qrN5FQdm9uA.en.vtt
553 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price-Ck4i1Yk4pT0.ar.vtt
553 Bytes
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.zh-CN.vtt
553 Bytes
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.en.vtt
553 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.zh-CN.vtt
553 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-2yo4xrFnDyg.es.vtt
552 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values-kNsdYqgn9Mk.zh-CN.vtt
552 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.zh-CN.vtt
552 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-j2SP83afRS0.zh-CN.vtt
552 Bytes
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.it.vtt
552 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.pt-BR.vtt
552 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.zh-CN.vtt
552 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-5tdFjuAX9u0.en.vtt
551 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means-kuTOS0wZJd4.en.vtt
551 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects-OxL-gMTizUA.pt-BR.vtt
551 Bytes
Part 13-Module 01-Lesson 07_Narrative Structures/34. Updated World Cup Data Set-tA_je-rSL7c.zh-CN.vtt
551 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/02. Action Time-80DSWU8ZUoQ.en.vtt
550 Bytes
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review-xzZZZCZk5YM.en.vtt
550 Bytes
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.en.vtt
549 Bytes
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-0ZBp8oWySAc.pt-BR.vtt
549 Bytes
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Window Functions Conclusion-2ZdocDMw7D8.zh-CN.vtt
549 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.ar.vtt
549 Bytes
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.en.vtt
549 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-FNKRumSym18.es.vtt
548 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.ar.vtt
548 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.th.vtt
548 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/11. What Is an Outlier-XP3F26GGuhE.en.vtt
547 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic-wDjjmYJ9Z5Y.zh-CN.vtt
547 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.pt-BR.vtt
547 Bytes
Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.zh-CN.vtt
547 Bytes
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-PYNWtLgtRfU.zh-CN.vtt
547 Bytes
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.zh-CN.vtt
547 Bytes
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.ar.vtt
547 Bytes
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.pt-BR.vtt
547 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.pt-BR.vtt
547 Bytes
Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings--laXTx9corQ.zh-CN.vtt
546 Bytes
Part 15-Module 01-Lesson 02_Design Principles/20. Onwards!-i-ulsdVHhCc.en.vtt
546 Bytes
Part 19-Module 01-Lesson 02_Design/22. Onwards!-i-ulsdVHhCc.en.vtt
546 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.ar.vtt
544 Bytes
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-bnwLadF8gKo.en.vtt
543 Bytes
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-cUhgZ2BnWq0.en.vtt
543 Bytes
Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-VD14oP-Ue6M.ar.vtt
543 Bytes
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.ar.vtt
543 Bytes
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-Njbmexuo7fo.zh-CN.vtt
543 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/18. Finches - Find t-Statistic-eAN4NfHSgk8.zh-CN.vtt
542 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-U3FUxkm1MxI.ar.vtt
542 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions-szqkEhERjDI.pt-BR.vtt
541 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score--Sw8Dlo0fx4.en.vtt
541 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM-4FAowd-l1p4.en.vtt
541 Bytes
Part 15-Module 01-Lesson 02_Design Principles/20. Onwards!-i-ulsdVHhCc.pt-BR.vtt
541 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.th.vtt
541 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.ja.vtt
541 Bytes
Part 17-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.pt-BR.vtt
541 Bytes
Part 19-Module 01-Lesson 02_Design/22. Onwards!-i-ulsdVHhCc.pt-BR.vtt
541 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/09. Operational Definition-khRQslIcqyY.es.vtt
540 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/09. Operational Definition-khRQslIcqyY.es.vtt
540 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-6K9Zztqbozw.en.vtt
540 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-dxw2VFq5sAc.en.vtt
540 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/17. Find Standard Error-ctx--oGjVgs.pt-BR.vtt
540 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size-tX7p7HXlKBQ.en.vtt
540 Bytes
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/09. L4_Mini Project-CGPO68cOCgc.pt-BR.vtt
540 Bytes
Part 11-Module 01-Lesson 09_Clustering/13. Some challenges of k-means-e2CdlG5P4WA.pt-BR.vtt
540 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.en.vtt
540 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-6K9Zztqbozw.pt-BR.vtt
539 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.ar.vtt
539 Bytes
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.zh-CN.vtt
539 Bytes
Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-PlFG87qPSB4.zh-CN.vtt
539 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/02. Accuracy Review-g3sxDtlGlAM.zh-CN.vtt
539 Bytes
Part 13-Module 01-Lesson 07_Narrative Structures/22. Narratives Summary-QFXxRlLETyI.zh-CN.vtt
539 Bytes
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.hr.vtt
539 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-2yo4xrFnDyg.en.vtt
538 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-xE00wGLivN4.en.vtt
538 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/14. Two-Tailed Critical Values 0.001-KD_AqWVG4Cc.en.vtt
538 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages-_0AHmKkfjTo.pt-BR.vtt
538 Bytes
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.ar.vtt
538 Bytes
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-5v1jxDIwGqk.pt-BR.vtt
538 Bytes
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.zh-CN.vtt
538 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.es-ES.vtt
538 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/10. Two-Tailed t-Test-5mxtx0yqlyM.pt-BR.vtt
537 Bytes
Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-q23Nlo1Rfn4.zh-CN.vtt
537 Bytes
Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-kIITzFRh5mQ.zh-CN.vtt
537 Bytes
Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-rexAHoCGFMs.zh-CN.vtt
537 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.en.vtt
537 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/38. Keyboards - Cohen's d-yejk0jbkWBk.en.vtt
536 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-T7rdBFQQ0Fw.ar.vtt
536 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-0PFq8zoaNWU.en.vtt
536 Bytes
Part 16-Module 03-Lesson 05_SQL Data Cleaning/08. CONCAT-bCxZnQN28Y4.zh-CN.vtt
536 Bytes
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.zh-CN.vtt
536 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-0PFq8zoaNWU.en.vtt
536 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-vsID16a_suU.pt-BR.vtt
535 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/17. Find Standard Error-ctx--oGjVgs.en.vtt
535 Bytes
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.ja.vtt
535 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-HAQ0-Skvzmc.ar.vtt
535 Bytes
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.es-ES.vtt
535 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-HAQ0-Skvzmc.ar.vtt
535 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-RIJpz1jXO4A.es.vtt
534 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/22. Popular Chris-VTgnBeCqHjE.pt-BR.vtt
534 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/03. Tetrahedral Die-WtGcIl_o_40.en.vtt
534 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region-SyNQ2mElRi0.en.vtt
534 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-bRhdim9PTFI.zh-CN.vtt
534 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-611qWzIxGmU.en.vtt
534 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-611qWzIxGmU.en.vtt
534 Bytes
Part 21-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.ar.vtt
534 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-YY31Ggi4XyQ.pt-BR.vtt
533 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20-W0R3XOK1IfE.en.vtt
533 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/29. Cohen's d-smedG3-3mOE.pt-BR.vtt
533 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.ar.vtt
533 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-0PFq8zoaNWU.pt-BR.vtt
533 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-HFCs3LbQ5Z0.zh-CN.vtt
533 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.ar.vtt
533 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.es-ES.vtt
533 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-0PFq8zoaNWU.pt-BR.vtt
533 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/11. Bounds of Area-eADm6bXU3_0.zh-CN.vtt
532 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.ar.vtt
532 Bytes
Part 13-Module 01-Lesson 04_Design Principles/44. Leland Wilkinson-w7TLo_X4sfY.zh-CN.vtt
532 Bytes
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.ja.vtt
532 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.ar.vtt
532 Bytes
Part 17-Module 01-Lesson 12_Hypothesis Testing/01. Hypothesis Testing Introduction-Qi6F2rJAmrA.zh-CN.vtt
532 Bytes
Part 17-Module 01-Lesson 13_Case Study AB tests/01. Case Study Introduction-J5uvdPxHIfs.zh-CN.vtt
532 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.en.vtt
531 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.en.vtt
531 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions-szqkEhERjDI.en.vtt
531 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-xBnhUJENAtk.pt-BR.vtt
531 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.zh-CN.vtt
531 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-aALYYSwS7MM.ar.vtt
531 Bytes
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.zh-CN.vtt
531 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.ja.vtt
531 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.es-ES.vtt
531 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-xBnhUJENAtk.es.vtt
530 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/01. Compare Sample Means-l9Sy4qoLHVo.pt-BR.vtt
530 Bytes
Part 11-Module 01-Lesson 09_Clustering/13. Some challenges of k-means-e2CdlG5P4WA.zh-CN.vtt
530 Bytes
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.hr.vtt
530 Bytes
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.pt-BR.vtt
530 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.en.vtt
530 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/13. Visualizing Data-tqXBhXfWiDE.nl.vtt
529 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/12. Define Outlier-jxatUS0YvtU.zh-CN.vtt
529 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/22. Popular Chris-VTgnBeCqHjE.en.vtt
529 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/23. Pooled Variance Sum of Squares-c0lWwW1Z9Ac.pt-BR.vtt
529 Bytes
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-GwzB76HYlFE.ar.vtt
529 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.zh-CN.vtt
529 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-Lb_v4vj3TNs.pt-BR.vtt
529 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.es-ES.vtt
529 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-Lb_v4vj3TNs.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/08. Where Is Q1-eLyI7n6GtbU.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/28. Avg. Squared Dev. in Words--_I23DcNTF0.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-a2GCyz_N0oY.zh-CN.vtt
528 Bytes
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare-B2KnUg5iz0Y.zh-CN.vtt
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Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-HH73nOnzRrc.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post-NtldeU_E4sI.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.ja.vtt
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/16. Subquery Conclusion-TUYvx2K9-5k.en.vtt
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Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.ja.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/02. Gambling in Vegas-qbcBbbm3lt8.zh-CN.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/03. Tetrahedral Die-l7p3uldaCks.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size-kKT56up4n_o.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-TpVxnYcI_uw.zh-CN.vtt
526 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.pt-BR.vtt
526 Bytes
Part 16-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions-Glctk6ahdFU.ar.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.pt-BR.vtt
526 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.ja.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region-skeY26k1hSs.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.en.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-_itWo-gUTzY.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-RIJpz1jXO4A.en.vtt
523 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/01. Social Networkers' Salaries-4nYdxMABeBc.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/20. Equation for Average Deviation-9jdZ9pfYP6A.zh-CN.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/07. More Detail-XUrP62LvciA.pt-BR.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/09. L4_Mini Project-CGPO68cOCgc.en.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results-tmAlVZCbgFA.pt-BR.vtt
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.en.vtt
523 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.pt-BR.vtt
523 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.pt-BR.vtt
523 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/18. Deviation from Mean-seTkSLAS43o.pt-BR.vtt
522 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/02. Probability-Wf7m7ygRvz8.en.vtt
522 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/37. Keyboards - Decision-PXDcczTlqLc.zh-CN.vtt
522 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/02. Action Time-80DSWU8ZUoQ.pt-BR.vtt
522 Bytes
Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-BGNx2FiNFY0.zh-CN.vtt
522 Bytes
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Window Functions Conclusion-2ZdocDMw7D8.pt-BR.vtt
522 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.zh-CN.vtt
522 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.zh-CN.vtt
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/18. 26. Video Games-SyszPG1615c.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.ar.vtt
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Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-8Ygq5dRV0Kk.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-eVAEO2QRdM0.zh-CN.vtt
521 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.zh-CN.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values-e2C4tEKNtqs.pt-BR.vtt
520 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.pt-BR.vtt
520 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/11. What Is an Outlier-GRLrzWwTz58.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-cJCx-Su6vx0.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-1jUwuW70lF0.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-YY31Ggi4XyQ.es.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/19. Standard Error for Avg of 5 Dice-RQ_AHYQTSDA.pt-BR.vtt
518 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/06. DF - Marginal Totals-ykVKAjC9_TA.zh-CN.vtt
518 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision-k1plVVNoyeY.en.vtt
518 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.pt-BR.vtt
518 Bytes
Part 16-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data-AJF5smH1TJU.en.vtt
518 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.ar.vtt
518 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.ar.vtt
518 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.es.vtt
517 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-FNKRumSym18.en.vtt
517 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/07. Sampling Distribution-kQevFvu_dL0.zh-CN.vtt
517 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region-skeY26k1hSs.en.vtt
517 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.pt-BR.vtt
517 Bytes
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.hr.vtt
517 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-xBnhUJENAtk.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-dxw2VFq5sAc.zh-CN.vtt
516 Bytes
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.zh-CN.vtt
516 Bytes
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.ar.vtt
516 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.es-ES.vtt
516 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/09. Operational Definition-khRQslIcqyY.en.vtt
515 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/09. Operational Definition-khRQslIcqyY.en.vtt
515 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends-swOg73wqLKM.pt-BR.vtt
515 Bytes
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line-O4jFvJWal6s.ar.vtt
515 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-hAPJsh81L98.zh-CN.vtt
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/02. Introduction-fxNSn63xFvA.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-Khxyqd5vtOo.zh-CN.vtt
513 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-9bsmO7cKzPk.pt-BR.vtt
513 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/04. Relative Frequency Histogram-1K7_1uPm8F8.en.vtt
513 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean-potr9cTBlxI.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-Jbqf8OBORDg.en.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-Jbqf8OBORDg.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.zh-CN.vtt
512 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/11. What Is an Outlier-XP3F26GGuhE.zh-CN.vtt
512 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.ar.vtt
512 Bytes
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-v2_aFAmQxfw.en.vtt
512 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-9bNGgRojUC0.ar.vtt
511 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-b7oUjvNJWCc.ar.vtt
511 Bytes
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.zh-CN.vtt
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Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-9J3IwQFXveI.ar.vtt
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Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-R0RqC-yerD4.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-4EpW5acw55c.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-3R0LfaKa-fw.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/29. Rent - Margin of Error-q413Zzil8lQ.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.ar.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.pt-BR.vtt
508 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/38. Keyboards - Cohen's d-yejk0jbkWBk.pt-BR.vtt
508 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.zh-CN.vtt
508 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.zh-CN.vtt
508 Bytes
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-cuBxHYSPrkA.ar.vtt
508 Bytes
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.en.vtt
508 Bytes
Part 21-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.pt-BR.vtt
508 Bytes
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/18. Conclusion-P7H8wjCIJ6k.en.vtt
507 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.en.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.pt-BR.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/19. Conclusion-P7H8wjCIJ6k.en.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/13. Katie - SDs Below-oV8f7eO_1hA.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-FNKRumSym18.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-80BAbiEWsaY.pt-BR.vtt
505 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/02. Guinness-6V5K3VOGp8c.pt-BR.vtt
505 Bytes
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.ar.vtt
505 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-611qWzIxGmU.zh-CN.vtt
505 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-611qWzIxGmU.zh-CN.vtt
505 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/10. Two-Tailed t-Test-5mxtx0yqlyM.en.vtt
504 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.zh-CN.vtt
504 Bytes
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel-yg5c1caIB4E.ar.vtt
504 Bytes
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.it.vtt
504 Bytes
Part 17-Module 01-Lesson 13_Case Study AB tests/18. Conclusion-qmGjRpMVBz8.zh-CN.vtt
504 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-6K9Zztqbozw.es.vtt
503 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular-SCy8YH5xu3Q.pt-BR.vtt
503 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null-qUcZFxEXz2I.pt-BR.vtt
503 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/29. Congrats-psVUIDdsbA0.zh-CN.vtt
503 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.zh-CN.vtt
503 Bytes
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/08. Further Learning-SnLQlP5J7c8.en.vtt
503 Bytes
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.pt-BR.vtt
503 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.zh-CN.vtt
503 Bytes
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review-xzZZZCZk5YM.zh-CN.vtt
503 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/08. Where Is Q1-0ZTaV6UATBI.pt-BR.vtt
502 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/29. Cohen's d-smedG3-3mOE.en.vtt
502 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.en.vtt
502 Bytes
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-Xrl2Hd--NWs.zh-CN.vtt
502 Bytes
Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-VEXUQmVpazE.zh-CN.vtt
502 Bytes
Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-4EpW5acw55c.en.vtt
502 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-5cs9badCyPQ.zh-CN.vtt
502 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.es-ES.vtt
502 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages-_0AHmKkfjTo.en.vtt
501 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.ja.vtt
501 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-aUc0FKD4834.ar.vtt
501 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.pt-BR.vtt
501 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis-u6vw-FcHT-M.en.vtt
500 Bytes
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-7ZvLztG6xhg.pt-BR.vtt
500 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.pt-BR.vtt
500 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/38. Something Fun-S3UsHyKkoww.pt-BR.vtt
499 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values-coHA_ziMiws.pt-BR.vtt
499 Bytes
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-Kn9v0KGDsvc.zh-CN.vtt
499 Bytes
Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-20QVVrTcp2A.zh-CN.vtt
499 Bytes
Part 17-Module 01-Lesson 13_Case Study AB tests/14. Analyzing Multiple Metrics-DtZghKNa7Ak.zh-CN.vtt
499 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/01. Social Networkers' Salaries-4nYdxMABeBc.pt-BR.vtt
498 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs-CtbwhKXSEMs.pt-BR.vtt
498 Bytes
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-0ZBp8oWySAc.zh-CN.vtt
498 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.pt-BR.vtt
498 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-cJCx-Su6vx0.es.vtt
497 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI-guhmjr4BqSo.zh-CN.vtt
497 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.pt-BR.vtt
497 Bytes
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-cUhgZ2BnWq0.zh-CN.vtt
497 Bytes
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.pt-BR.vtt
497 Bytes
Part 16-Module 03-Lesson 05_SQL Data Cleaning/17. Data Cleaning Conclusion-KkHqnvD9BWY.en.vtt
497 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.pt-BR.vtt
497 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.ar.vtt
497 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-RIJpz1jXO4A.pt-BR.vtt
496 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/02. Action Time-80DSWU8ZUoQ.zh-CN.vtt
496 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.ar.vtt
496 Bytes
Part 13-Module 01-Lesson 04_Design Principles/32. Do No Harm-BIQPOMfDXjs.pt-BR.vtt
496 Bytes
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.pt-BR.vtt
496 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.en.vtt
496 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.zh-CN.vtt
495 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.zh-CN.vtt
495 Bytes
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/13. Series Indexes-FA4mkuoDoJI.en.vtt
495 Bytes
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/18. Conclusion-P7H8wjCIJ6k.zh-CN.vtt
495 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-X_5v9jxuLrQ.en.vtt
495 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.en.vtt
495 Bytes
Part 13-Module 01-Lesson 04_Design Principles/43. Calculating the Lie Factor-U3ZnXlDS5No.ar.vtt
495 Bytes
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.en.vtt
495 Bytes
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.zh-CN.vtt
495 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.pt-BR.vtt
495 Bytes
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/14. Series Indexes-FA4mkuoDoJI.en.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/19. Conclusion-P7H8wjCIJ6k.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-1jUwuW70lF0.es.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1-tYaQItpvXUo.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means-kuTOS0wZJd4.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/21. Visualize P-Value-Za4LLPiE7pI.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.ja.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-i7pRvuVoWg0.ar.vtt
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Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-v2_aFAmQxfw.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-7ZvLztG6xhg.en.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/13. Series Indexes-FA4mkuoDoJI.pt-BR.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.ar.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.es-ES.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/14. Series Indexes-FA4mkuoDoJI.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-1jUwuW70lF0.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-80BAbiEWsaY.es.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score--Sw8Dlo0fx4.zh-CN.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/02. Probability-Wf7m7ygRvz8.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.ja.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/39. Keyboards - CI for Dependent Samples-POKBAWQ2S7U.pt-BR.vtt
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Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ZlDdxWYv6jw.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-Lb_v4vj3TNs.en.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.ar.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.ja.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-Lb_v4vj3TNs.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/08. Where Is Q1-eLyI7n6GtbU.pt-BR.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-AF07y1oAim0.ar.vtt
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Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-FpQm_dYA9LM.ar.vtt
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Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-5v1jxDIwGqk.en.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-n7gp8USw0Jw.zh-CN.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/31. Good Job!-ZZoeeLpWcmU.ar.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/23. Critical Values 0.05-P-CGd_Vzpk0.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value-qrN5FQdm9uA.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.en.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/14. -E-Bd6EEl20s.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/23. Rent - t-Critical Values-WTmFRvH2AmI.pt-BR.vtt
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Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-Jbqf8OBORDg.pt-BR.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-Jbqf8OBORDg.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.ja.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-cJCx-Su6vx0.zh-CN.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score-JdzOGxmq2jE.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.en.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions-Glctk6ahdFU.pt-BR.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-7umkXt9U5lE.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-7umkXt9U5lE.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/17. Find Standard Error-ctx--oGjVgs.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.zh-CN.vtt
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/09. L4_Mini Project-CGPO68cOCgc.zh-CN.vtt
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Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.zh-CN.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/14. Dependent Variable-QyKOEh0722A.en.vtt
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Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.zh-CN.vtt
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Part 17-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/13. SD of Sampling Distribution-rJ8NsbL5iTk.zh-CN.vtt
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Part 05-Module 01-Lesson 05_Data Quality/20. Conclusion-fSwaNltHTio.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.pt-BR.vtt
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Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-f_SBhjbfmPw.pt-BR.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.en.vtt
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Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-2FQu07aKLwg.ar.vtt
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Part 13-Module 01-Lesson 02_D3 Building Blocks/16. -6-NsyLPx738.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/32. Do No Harm-BIQPOMfDXjs.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-l7P-e1M_qPA.zh-CN.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.ja.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-jP1KfLaTtpU.ar.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-f_SBhjbfmPw.en.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.en-US.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.pt-BR.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.en-US.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.pt-BR.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-jP1KfLaTtpU.ar.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/18. Deviation from Mean-seTkSLAS43o.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.ar.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-FNKRumSym18.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/04. DF - Choose n Numbers-4XEJJC-vSRw.pt-BR.vtt
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Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-bUvlDsmmpIo.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.es-ES.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.th.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-xE00wGLivN4.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-YY31Ggi4XyQ.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-xBnhUJENAtk.zh-CN.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/08. Probability Mean or = 3-JSlSjQwhIAI.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.ar.vtt
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Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-FY0DXe0lfrI.ar.vtt
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/21. Visualization design -TTGYKv5Qta0.en.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-6K9Zztqbozw.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions-szqkEhERjDI.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.ja.vtt
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Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-R0RqC-yerD4.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-FwaYsmnlLM4.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.es-ES.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-FwaYsmnlLM4.pt-BR.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post-NtldeU_E4sI.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/12. Ratio of SDs-E14J3Thd0lc.zh-CN.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects-OxL-gMTizUA.en.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.ja.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-QeTWVPi1Evo.ar.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.it.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/27. Klout Parameters-CLGwm6tBHlk.pt-BR.vtt
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Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.ar.vtt
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Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-jJSkp9n3kA8.en.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-bnwLadF8gKo.zh-CN.vtt
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Part 07-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages-_0AHmKkfjTo.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.en.vtt
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Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-wnIQ6fCVD40.ar.vtt
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Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.en.vtt
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Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.es-ES.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.ja.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.pt-BR.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.pt-BR.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/33. Congrats-Qy8VYdqoxGA.zh-CN.vtt
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Part 21-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/03. Tetrahedral Die-l7p3uldaCks.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/18. Finches - Find t-Statistic-nBqsiW5r-98.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-e_8DmUBHAao.ja.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.ja.vtt
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Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ZlDdxWYv6jw.en.vtt
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Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.en.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.en-US.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/25. Bar Chart Issues-MNsMZH1Y0Js.pt-BR.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data-AJF5smH1TJU.zh-CN.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.ar.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.en-US.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/26. Sum of Squares-Vr3knoVJvlk.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/28. Avg. Squared Dev. in Words--_I23DcNTF0.en.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-HWW9BNHnPo0.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.es-ES.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.es-ES.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-HWW9BNHnPo0.ar.vtt
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Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.en.vtt
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Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-R0RqC-yerD4.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-9bsmO7cKzPk.es.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-NcWS_BvM3IU.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/08. Where Is Q1-0ZTaV6UATBI.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-vsID16a_suU.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/19. Standard Error for Avg of 5 Dice-RQ_AHYQTSDA.en.vtt
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Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-9AVeGkUcPYQ.pt-BR.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/19. Outro-q7a9w02Uepw.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.ja.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.en.vtt
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Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.hr.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/28. Meaningful Results-yexyfs5ca2k.pt-BR.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values-coHA_ziMiws.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.en.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.en.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.en.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.en.vtt
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/09. 25. Caffeine--D3nyKUK1kY.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-jJSkp9n3kA8.ko.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-Jbqf8OBORDg.zh-CN.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-Jbqf8OBORDg.zh-CN.vtt
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Part 21-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.en.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/13. Katie - SDs Below-oV8f7eO_1hA.en.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/22. Popular Chris-VTgnBeCqHjE.zh-CN.vtt
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Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-8SqL0v_FSsc.ja.vtt
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Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.ja.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.es-ES.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.pt-BR.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262-c6PzC3WZD4I.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/14. Dependent Variable-QyKOEh0722A.pt-BR.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/24. Calculate Pooled Variance-evwkqnO9BHY.pt-BR.vtt
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Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-3RuKO3PQWg0.ar.vtt
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Part 15-Module 01-Lesson 04_Telling Stories with Tableau/01. Communicating with your data-KDnca1zszIo.en.vtt
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/01. Communicating With Your Data-KDnca1zszIo.en.vtt
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Part 05-Module 02-Lesson 05_Deeper into SQL/19. Outro-q7a9w02Uepw.en-US.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.ar.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/08. Where Is Q1-eLyI7n6GtbU.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/26. Sum of Squares-Vr3knoVJvlk.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends-swOg73wqLKM.en.vtt
462 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/23. Critical Values 0.05-P-CGd_Vzpk0.en.vtt
462 Bytes
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-WDADret_QqE.en.vtt
462 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.ar.vtt
462 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.ar.vtt
462 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-5tdFjuAX9u0.zh-CN.vtt
461 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/25. Squared Deviations-mVBWg3aPPhI.en.vtt
461 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/13. Katie - SDs Below-COHUHzCELK4.pt-BR.vtt
461 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size-VXH1be4d1Nc.en.vtt
461 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-b7oUjvNJWCc.ja.vtt
461 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.pt-BR.vtt
461 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.en.vtt
461 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/01. Social Networkers' Salaries-4nYdxMABeBc.zh-CN.vtt
460 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/23. Pooled Variance Sum of Squares-c0lWwW1Z9Ac.en.vtt
460 Bytes
Part 05-Module 02-Lesson 05_Deeper into SQL/19. Outro-q7a9w02Uepw.en.vtt
460 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-U3FUxkm1MxI.pt-BR.vtt
460 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.zh-CN.vtt
460 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.zh-CN.vtt
460 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/01. t-Distribution-TC2Ro6pFAqA.en.vtt
459 Bytes
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/08. Troubleshooting With Appending-KwtjTmDMZGE.ar.vtt
459 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.ar.vtt
459 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.es-ES.vtt
459 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-VLgrNOLomc0.es-ES.vtt
458 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-VLgrNOLomc0.es-ES.vtt
458 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.zh-CN.vtt
458 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.en.vtt
458 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-AjI84ujXBHk.ar.vtt
458 Bytes
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-8Ygq5dRV0Kk.en.vtt
458 Bytes
Part 16-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results-tmAlVZCbgFA.en.vtt
458 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.ja.vtt
458 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.zh-CN.vtt
458 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/14. Acne Medication - Decision-WzwHLFlkxVA.pt-BR.vtt
457 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-AF07y1oAim0.pt-BR.vtt
457 Bytes
Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-VD14oP-Ue6M.pt-BR.vtt
457 Bytes
Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.en.vtt
457 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/07. More Detail-XUrP62LvciA.en.vtt
456 Bytes
Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-9AVeGkUcPYQ.en.vtt
456 Bytes
Part 06-Module 01-Lesson 01_Working with MongoDB/30. Conclusion-mjPfjzOWiDw.pt-BR.vtt
456 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-e_8DmUBHAao.pt-BR.vtt
456 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.zh-CN.vtt
456 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-_itWo-gUTzY.zh-CN.vtt
456 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.it.vtt
456 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.ar.vtt
456 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.zh-CN.vtt
456 Bytes
Part 18-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 -dRbjnKOnd0Y.ar.vtt
456 Bytes
Part 21-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.zh-CN.vtt
456 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-RIJpz1jXO4A.zh-CN.vtt
455 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null-qUcZFxEXz2I.en.vtt
455 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/33. Keyboards Point Estimate for Difference-Rw3QBEnIlJY.pt-BR.vtt
455 Bytes
Part 06-Module 01-Lesson 01_Working with MongoDB/30. Conclusion-mjPfjzOWiDw.en.vtt
455 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-CMIM_Ocu8vg.ar.vtt
455 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.es-ES.vtt
455 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.en.vtt
455 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-CMIM_Ocu8vg.ar.vtt
455 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-2yo4xrFnDyg.zh-CN.vtt
454 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-1GuHNqJNY2M.pt-BR.vtt
454 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-b7oUjvNJWCc.pt-BR.vtt
454 Bytes
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-O5B-Z5SUoc8.zh-CN.vtt
454 Bytes
Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-ZMfwPUrOFsE.pt-BR.vtt
454 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.pt-BR.vtt
454 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-1GuHNqJNY2M.es.vtt
453 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-X_5v9jxuLrQ.pt-BR.vtt
453 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2-It6AEuSDQw0.pt-BR.vtt
453 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-8SqL0v_FSsc.en.vtt
453 Bytes
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.hr.vtt
453 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.en.vtt
453 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-7umkXt9U5lE.es.vtt
452 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-7umkXt9U5lE.es.vtt
452 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/04. Relative Frequency Histogram-1K7_1uPm8F8.zh-CN.vtt
452 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/39. Keyboards - CI for Dependent Samples-POKBAWQ2S7U.en.vtt
452 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region-SyNQ2mElRi0.zh-CN.vtt
452 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.pt-BR.vtt
452 Bytes
Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-b1V_L3qFIUk.ar.vtt
452 Bytes
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/15. Conclusion-PXBdIBgFTL4.en.vtt
452 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.it.vtt
452 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/09. Operational Definition-khRQslIcqyY.zh-CN.vtt
451 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/09. Operational Definition-khRQslIcqyY.zh-CN.vtt
451 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/26. Sum of Squares-Vr3knoVJvlk.zh-CN.vtt
451 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/23. Rent - t-Critical Values-WTmFRvH2AmI.en.vtt
451 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.ja.vtt
451 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-8SqL0v_FSsc.pt-BR.vtt
451 Bytes
Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-ZMfwPUrOFsE.en.vtt
451 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-0PFq8zoaNWU.zh-CN.vtt
451 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.es-ES.vtt
451 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-0PFq8zoaNWU.zh-CN.vtt
451 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-80BAbiEWsaY.en.vtt
450 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/18. Finches - Find t-Statistic-nBqsiW5r-98.en.vtt
450 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision-fgg81QJg89s.en.vtt
450 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price-Ck4i1Yk4pT0.ja.vtt
450 Bytes
Part 13-Module 01-Lesson 04_Design Principles/32. Do No Harm-BIQPOMfDXjs.zh-CN.vtt
450 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision-fgg81QJg89s.pt-BR.vtt
449 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price-Ck4i1Yk4pT0.en-US.vtt
449 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.en.vtt
449 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-FwaYsmnlLM4.en.vtt
449 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.ja.vtt
449 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-FwaYsmnlLM4.en.vtt
449 Bytes
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/15. Conclusion-PXBdIBgFTL4.pt-BR.vtt
448 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/13. Visualizing Data-tqXBhXfWiDE.es.vtt
447 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262-c6PzC3WZD4I.pt-BR.vtt
447 Bytes
Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-QTq9pGMoZAE.ar.vtt
447 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.pt-BR.vtt
447 Bytes
Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-xPDk70gKkjk.ar.vtt
447 Bytes
Part 11-Module 01-Lesson 07_Regressions/16. Handoff to Katie-M3Nwl_B_bZ8.ar.vtt
447 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.pt-BR.vtt
447 Bytes
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.th.vtt
447 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/38. Something Fun-S3UsHyKkoww.en.vtt
446 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.ar.vtt
446 Bytes
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/16. Subquery Conclusion-TUYvx2K9-5k.zh-CN.vtt
446 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/16. Roll 2 Dice-D4bQbaCAUoE.pt-BR.vtt
445 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/34. Keyboards - SD of Differences-Ej8yntoeBw0.en.vtt
445 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test-AXYl4jWsA3o.pt-BR.vtt
445 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price-Ck4i1Yk4pT0.en.vtt
445 Bytes
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-WDADret_QqE.pt-BR.vtt
445 Bytes
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.ar.vtt
445 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/16. Roll 2 Dice-D4bQbaCAUoE.en.vtt
444 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning-DKxww0fCCAA.pt-BR.vtt
444 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values-e2C4tEKNtqs.en.vtt
444 Bytes
Part 05-Module 01-Lesson 05_Data Quality/20. Conclusion-fSwaNltHTio.en.vtt
444 Bytes
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-uC1Xwc7warg.ar.vtt
444 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.it.vtt
444 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.ja.vtt
444 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.pt-BR.vtt
444 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis-Pk_BMZINZ0k.en.vtt
443 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/14. Acne Medication - Decision-WzwHLFlkxVA.en.vtt
443 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.ja.vtt
443 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.en.vtt
442 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.en.vtt
442 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/19. Average Deviation-OCLlqMAbxBM.pt-BR.vtt
442 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/09. Continuous Distribution-IncW1Q44jMk.pt-BR.vtt
442 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/11. Relationship Between SDs-8mHK1E3mR4E.pt-BR.vtt
442 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.en.vtt
442 Bytes
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.zh-CN.vtt
442 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.pt-BR.vtt
442 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample-I487nBkmUoM.es.vtt
441 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/18. Better Sample-I487nBkmUoM.es.vtt
441 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/13. Visualizing Data-tqXBhXfWiDE.pt-BR.vtt
441 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/34. Does Low Probability = Causation-KaBa9N2TdnQ.pt-BR.vtt
441 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.th.vtt
441 Bytes
Part 17-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.zh-CN.vtt
441 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-ObSZnD336CA.pt-BR.vtt
440 Bytes
Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-9AVeGkUcPYQ.zh-CN.vtt
440 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-b7oUjvNJWCc.en.vtt
440 Bytes
Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.zh-CN.vtt
440 Bytes
Part 16-Module 03-Lesson 05_SQL Data Cleaning/17. Data Cleaning Conclusion-KkHqnvD9BWY.zh-CN.vtt
440 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.pt-BR.vtt
440 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-VLgrNOLomc0.en.vtt
439 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-VLgrNOLomc0.en.vtt
439 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean-potr9cTBlxI.en.vtt
439 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment-Q8hPJD_wXFY.en.vtt
439 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/28. Meaningful Results-yexyfs5ca2k.en.vtt
439 Bytes
Part 05-Module 01-Lesson 03_Data in More Complex Formats/01. Welcome to Lesson 2-53b_nnGcnBY.pt-BR.vtt
439 Bytes
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-8Ygq5dRV0Kk.pt-BR.vtt
439 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.es.vtt
438 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.es.vtt
438 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular-SCy8YH5xu3Q.en.vtt
438 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects-OxL-gMTizUA.zh-CN.vtt
438 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.ar.vtt
438 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/13. Visualizing Data-tqXBhXfWiDE.zh-CN.vtt
437 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/27. Klout Parameters-CLGwm6tBHlk.en.vtt
437 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/16. Mean Number of Shoes-DtdsK8K1OtI.en.vtt
437 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-e_8DmUBHAao.en.vtt
437 Bytes
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.ar.vtt
437 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score-JdzOGxmq2jE.en.vtt
436 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20-W0R3XOK1IfE.zh-CN.vtt
436 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.en.vtt
436 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.pt-BR.vtt
436 Bytes
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-pt_S3HwE5GY.ar.vtt
436 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.ar.vtt
436 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-vsID16a_suU.zh-CN.vtt
435 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/25. Squared Deviations-mVBWg3aPPhI.pt-BR.vtt
435 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less-wDRJK3htUZE.zh-CN.vtt
435 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2-It6AEuSDQw0.en.vtt
435 Bytes
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.en.vtt
435 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-T7rdBFQQ0Fw.pt-BR.vtt
435 Bytes
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.it.vtt
435 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/13. Visualizing Data-tqXBhXfWiDE.en.vtt
434 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-0r9S6UNDRu8.hi.vtt
434 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.ja.vtt
434 Bytes
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/23. L3 outro-y46uDftUXHo.zh-CN.vtt
434 Bytes
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/47. What's Next-y46uDftUXHo.zh-CN.vtt
434 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-YetpTU5SmUg.pt-BR.vtt
433 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-1GuHNqJNY2M.en.vtt
433 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/25. Squared Deviations-mVBWg3aPPhI.zh-CN.vtt
433 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/34. Prone to Misinterpretations-DUVB_GCcado.en.vtt
433 Bytes
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Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.en.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.it.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.pt-BR.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error-22SXauLJVd4.pt-BR.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic-LDdm06-FHYI.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/01. Welcome to Lesson 2-53b_nnGcnBY.zh-CN.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price--P5lMGuVA6U.ja.vtt
432 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-aUc0FKD4834.pt-BR.vtt
432 Bytes
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/01. Communicating with your data-KDnca1zszIo.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.en.vtt
432 Bytes
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/01. Communicating With Your Data-KDnca1zszIo.zh-CN.vtt
432 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-1jUwuW70lF0.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null-qUcZFxEXz2I.zh-CN.vtt
431 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/02. Guinness-6V5K3VOGp8c.en.vtt
431 Bytes
Part 05-Module 02-Lesson 05_Deeper into SQL/19. Outro-q7a9w02Uepw.pt-BR.vtt
431 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-i7pRvuVoWg0.ja.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-9frwavCQvGg.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.zh-CN.vtt
431 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/08. Where Is Q1-0ZTaV6UATBI.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/19. Average Deviation-OCLlqMAbxBM.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262-c6PzC3WZD4I.zh-CN.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs-CtbwhKXSEMs.en.vtt
430 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis-u6vw-FcHT-M.zh-CN.vtt
430 Bytes
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/13. Series Indexes-FA4mkuoDoJI.zh-CN.vtt
430 Bytes
Part 16-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions-Glctk6ahdFU.en.vtt
430 Bytes
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/14. Series Indexes-FA4mkuoDoJI.zh-CN.vtt
430 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/27. Average Squared Deviation-kmVqaJ6n9Vk.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/10. Two-Tailed t-Test-5mxtx0yqlyM.zh-CN.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/14. Dependent Variable-QyKOEh0722A.zh-CN.vtt
429 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price-Ck4i1Yk4pT0.pt-BR.vtt
429 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test-AXYl4jWsA3o.en.vtt
428 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-T7rdBFQQ0Fw.en.vtt
428 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/25. Bar Chart Issues-MNsMZH1Y0Js.en.vtt
428 Bytes
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/23. L3 outro-y46uDftUXHo.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.ja.vtt
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/47. What's Next-y46uDftUXHo.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-dXS9vjgXyg4.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/25. Rent - Decision-edm9jPvzeAc.pt-BR.vtt
427 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.pt-BR.vtt
427 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.en.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-7umkXt9U5lE.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-7umkXt9U5lE.en.vtt
426 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment-Q8hPJD_wXFY.pt-BR.vtt
426 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.zh-CN.vtt
426 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price-Ck4i1Yk4pT0.zh-CN.vtt
426 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.pt-BR.vtt
426 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.zh-CN.vtt
426 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/25. Bar Chart Issues-MNsMZH1Y0Js.zh-CN.vtt
426 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.es-ES.vtt
426 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.zh-CN.vtt
426 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size-tl4mqs0SqX4.pt-BR.vtt
425 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/33. Keyboards Point Estimate for Difference-Rw3QBEnIlJY.en.vtt
425 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.ja.vtt
425 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.zh-CN.vtt
425 Bytes
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.ar.vtt
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Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.ar.vtt
425 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-Lb_v4vj3TNs.zh-CN.vtt
425 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.hr.vtt
425 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.en.vtt
425 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.es-ES.vtt
425 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-Lb_v4vj3TNs.zh-CN.vtt
425 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/27. Average Squared Deviation-kmVqaJ6n9Vk.pt-BR.vtt
424 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.ja.vtt
424 Bytes
Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-ZMfwPUrOFsE.zh-CN.vtt
424 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.es-ES.vtt
424 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.en.vtt
424 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-ObSZnD336CA.es.vtt
423 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis-u6vw-FcHT-M.pt-BR.vtt
423 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/03. Assessing the Quality of Data Pt. 1-Dezhyk312lQ.en.vtt
423 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.ar.vtt
423 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-DzyOcsBIncA.ar.vtt
423 Bytes
Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-maL-S68XvTc.ar.vtt
423 Bytes
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/08. Further Learning-SnLQlP5J7c8.zh-CN.vtt
423 Bytes
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.th.vtt
423 Bytes
Part 21-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.en.vtt
423 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/18. Deviation from Mean-M43NnIroHws.pt-BR.vtt
422 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/18. Deviation from Mean-seTkSLAS43o.zh-CN.vtt
422 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/13. Katie - SDs Below-COHUHzCELK4.en.vtt
422 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.ar.vtt
422 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.en.vtt
422 Bytes
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.zh-CN.vtt
422 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-QWWq77k-K_0.ar.vtt
422 Bytes
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.zh-CN.vtt
422 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.it.vtt
422 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.pt-BR.vtt
422 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-QWWq77k-K_0.ar.vtt
422 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-LCrrPfsXaVc.pt-BR.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/04. Probability Greater-5DZTwMn7GAY.pt-BR.vtt
421 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/29. Rent - Margin of Error-nHF7LgYaZnE.en.vtt
421 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/34. Keyboards - SD of Differences-Ej8yntoeBw0.pt-BR.vtt
421 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/03. Assessing the Quality of Data Pt. 1-Dezhyk312lQ.pt-BR.vtt
421 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.ar.vtt
421 Bytes
Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-VD14oP-Ue6M.en.vtt
421 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.pt-BR.vtt
421 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/11. Relationship Between SDs-8mHK1E3mR4E.en.vtt
420 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/28. Meaningful Results-yexyfs5ca2k.zh-CN.vtt
420 Bytes
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-jP1KfLaTtpU.pt-BR.vtt
420 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.zh-CN.vtt
420 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.ar.vtt
420 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.ja.vtt
420 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.zh-CN.vtt
420 Bytes
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-jP1KfLaTtpU.pt-BR.vtt
420 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.pt-BR.vtt
419 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.pt-BR.vtt
419 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-U3FUxkm1MxI.en.vtt
419 Bytes
Part 11-Module 01-Lesson 03_SVM/09. Handoff to Katie-GkqOdgZnkig.ar.vtt
419 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.en.vtt
419 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-oTAhEKrWq2g.ar.vtt
419 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.ja.vtt
419 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-9bsmO7cKzPk.en.vtt
418 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.en.vtt
418 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.zh-CN.vtt
417 Bytes
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-qhhrjvLF8H8.pt-BR.vtt
417 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/28. Avg. Squared Dev. in Words--_I23DcNTF0.zh-CN.vtt
417 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/01. Compare Sample Means-l9Sy4qoLHVo.en.vtt
417 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/03. Tetrahedral Die-WtGcIl_o_40.zh-CN.vtt
417 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/17. Check You Out-tgni8KzxWzA.pt-BR.vtt
417 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.pt-BR.vtt
417 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.pt-BR.vtt
417 Bytes
Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-4EpW5acw55c.zh-CN.vtt
417 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.es-ES.vtt
417 Bytes
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.ja.vtt
417 Bytes
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-8SqL0v_FSsc.zh-CN.vtt
416 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.zh-CN.vtt
416 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.ja.vtt
416 Bytes
Part 15-Module 01-Lesson 02_Design Principles/20. Onwards!-i-ulsdVHhCc.zh-CN.vtt
416 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.en.vtt
416 Bytes
Part 19-Module 01-Lesson 02_Design/22. Onwards!-i-ulsdVHhCc.zh-CN.vtt
416 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-47JDwoDUxP8.en.vtt
415 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/12. Two-Tailed Probability-68_OkDcn6dI.pt-BR.vtt
415 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/14. Two-Tailed Critical Values 0.001-KD_AqWVG4Cc.zh-CN.vtt
415 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/34. Prone to Misinterpretations-DUVB_GCcado.pt-BR.vtt
415 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/29. Rent - Margin of Error-nHF7LgYaZnE.pt-BR.vtt
415 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/21. t-Critical-9-yTPJl_DIw.en.vtt
415 Bytes
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line-O4jFvJWal6s.en.vtt
415 Bytes
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line-O4jFvJWal6s.pt-BR.vtt
415 Bytes
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-f_SBhjbfmPw.zh-CN.vtt
415 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.ja.vtt
415 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.th.vtt
415 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/18. Deviation from Mean-M43NnIroHws.en.vtt
414 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/07. Significance-f0ZWCaOKW1Q.pt-BR.vtt
414 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-e_8DmUBHAao.zh-CN.vtt
414 Bytes
Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ZlDdxWYv6jw.zh-CN.vtt
414 Bytes
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/21. Visualization design -TTGYKv5Qta0.zh-CN.vtt
414 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.it.vtt
414 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.en.vtt
414 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-47JDwoDUxP8.pt-BR.vtt
413 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/11. What Is an Outlier-GRLrzWwTz58.pt-BR.vtt
413 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/36. Find Values-JP-mQPN9Sl4.en.vtt
413 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/13. Katie - SDs Below-oV8f7eO_1hA.zh-CN.vtt
413 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size-kKT56up4n_o.zh-CN.vtt
413 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error-ZU9uRiqLgxA.en.vtt
413 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-V0FNwMKhIVM.ar.vtt
413 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic-AeByX89sS4g.pt-BR.vtt
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/01. Welcome to Lesson 2-53b_nnGcnBY.en.vtt
412 Bytes
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-cuBxHYSPrkA.en.vtt
412 Bytes
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-LoLj_Ecohew.ar.vtt
412 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.es-ES.vtt
412 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/25. Rent - Decision-edm9jPvzeAc.en.vtt
411 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/38. Keyboards - Cohen's d-yejk0jbkWBk.zh-CN.vtt
411 Bytes
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.ar.vtt
411 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.zh-CN.vtt
411 Bytes
Part 21-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.pt-BR.vtt
411 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-ObSZnD336CA.en.vtt
410 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/02. Guinness-6V5K3VOGp8c.zh-CN.vtt
410 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM-4FAowd-l1p4.zh-CN.vtt
410 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/26. t-Statistic-P4tyKSWJUZc.pt-BR.vtt
410 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-9bNGgRojUC0.pt-BR.vtt
410 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2-It6AEuSDQw0.zh-CN.vtt
410 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-aALYYSwS7MM.ja.vtt
410 Bytes
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.pt-BR.vtt
410 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-0E08XPKeRNg.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.pt-BR.vtt
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Part 21-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.zh-CN.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/36. Find Values-JP-mQPN9Sl4.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/39. Keyboards - CI for Dependent Samples-POKBAWQ2S7U.zh-CN.vtt
409 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-i7pRvuVoWg0.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.zh-CN.vtt
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Part 16-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results-tmAlVZCbgFA.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.it.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-YetpTU5SmUg.en.vtt
408 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/11. What Is an Outlier-GRLrzWwTz58.en.vtt
408 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post-p-ma7uqFNCM.pt-BR.vtt
408 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error-sYOGafbS30Q.pt-BR.vtt
408 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-9bNGgRojUC0.en.vtt
408 Bytes
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-WDADret_QqE.zh-CN.vtt
408 Bytes
Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.zh-CN.vtt
408 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-2cUiqlbt-hc.ar.vtt
408 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.zh-CN.vtt
408 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.zh-CN.vtt
408 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-2cUiqlbt-hc.ar.vtt
408 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-LHLgEooUT4E.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-r2s9INGd-Ls.pt-BR.vtt
407 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error-ZU9uRiqLgxA.pt-BR.vtt
407 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-b7oUjvNJWCc.zh-CN.vtt
407 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-aUc0FKD4834.en.vtt
407 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01-6RNfHbEL4ZQ.pt-BR.vtt
406 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/21. Visualize P-Value-Za4LLPiE7pI.en.vtt
406 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/17. Check You Out-tgni8KzxWzA.en.vtt
406 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.ar.vtt
406 Bytes
Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-FpQm_dYA9LM.en.vtt
406 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-HWW9BNHnPo0.pt-BR.vtt
406 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.es-ES.vtt
406 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-HWW9BNHnPo0.pt-BR.vtt
406 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-dXS9vjgXyg4.en-US.vtt
405 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends-swOg73wqLKM.zh-CN.vtt
405 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size-VXH1be4d1Nc.zh-CN.vtt
405 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size-tl4mqs0SqX4.en.vtt
405 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/24. t-Statistic-KmEfiWATLUI.pt-BR.vtt
405 Bytes
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-GwzB76HYlFE.pt-BR.vtt
405 Bytes
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.pt-BR.vtt
405 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.en.vtt
405 Bytes
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-v2_aFAmQxfw.zh-CN.vtt
405 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-HAQ0-Skvzmc.pt-BR.vtt
405 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.ar.vtt
405 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-HAQ0-Skvzmc.pt-BR.vtt
405 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/32. Compute CI-Adzhg-M3Pvk.pt-BR.vtt
404 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-i7pRvuVoWg0.en.vtt
404 Bytes
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-5v1jxDIwGqk.zh-CN.vtt
404 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.ar.vtt
404 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-6pxpT3bZI54.pt-BR.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-dXS9vjgXyg4.en.vtt
403 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment-Q8hPJD_wXFY.zh-CN.vtt
403 Bytes
Part 06-Module 01-Lesson 01_Working with MongoDB/30. Conclusion-mjPfjzOWiDw.zh-CN.vtt
403 Bytes
Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-ZmDbDYoRxwQ.ar.vtt
403 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.ja.vtt
403 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.zh-CN.vtt
403 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.zh-CN.vtt
403 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/02. Mean of Treated Population-jC4--44m3-I.en.vtt
402 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/03. Assessing the Quality of Data Pt. 1-Dezhyk312lQ.zh-CN.vtt
402 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price--P5lMGuVA6U.ar.vtt
402 Bytes
Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-FpQm_dYA9LM.pt-BR.vtt
402 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-XN1eS7boCNg.ar.vtt
402 Bytes
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-7ZvLztG6xhg.zh-CN.vtt
402 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-XN1eS7boCNg.ar.vtt
402 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-VLgrNOLomc0.zh-CN.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-VLgrNOLomc0.zh-CN.vtt
401 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-80BAbiEWsaY.zh-CN.vtt
401 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/04. Probability Greater-5DZTwMn7GAY.en.vtt
401 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-jJSkp9n3kA8.zh-CN.vtt
401 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/07. Significance-f0ZWCaOKW1Q.en.vtt
401 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/23. Critical Values 0.05-P-CGd_Vzpk0.zh-CN.vtt
401 Bytes
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.zh-CN.vtt
401 Bytes
Part 16-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions-Glctk6ahdFU.zh-CN.vtt
401 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.pt-BR.vtt
401 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post-p-ma7uqFNCM.en.vtt
400 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis-Pk_BMZINZ0k.pt-BR.vtt
400 Bytes
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-GwzB76HYlFE.en.vtt
400 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.zh-CN.vtt
400 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/19. Between 10 and 16-lMm_BrpheLM.pt-BR.vtt
399 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/21. t-Critical-9-yTPJl_DIw.pt-BR.vtt
399 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic-LDdm06-FHYI.en.vtt
399 Bytes
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-jP1KfLaTtpU.en.vtt
399 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.en.vtt
399 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.zh-CN.vtt
399 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.ar.vtt
399 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.en.vtt
399 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.ar.vtt
399 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.zh-CN.vtt
399 Bytes
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-jP1KfLaTtpU.en.vtt
399 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis-kW_p0VHNEPM.en.vtt
398 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic-AeByX89sS4g.en.vtt
398 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/17. Check You Out-tgni8KzxWzA.zh-CN.vtt
398 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.ja.vtt
398 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.ja.vtt
398 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.th.vtt
398 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/07. More Detail-XUrP62LvciA.zh-CN.vtt
397 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular-SCy8YH5xu3Q.zh-CN.vtt
397 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.en.vtt
397 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.en.vtt
397 Bytes
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.ja.vtt
397 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.pt-BR.vtt
397 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-VkZ-W3kh9PA.pt-BR.vtt
396 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-YY31Ggi4XyQ.zh-CN.vtt
396 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.pt-BR.vtt
396 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.zh-CN.vtt
396 Bytes
Part 13-Module 01-Lesson 04_Design Principles/42. Size of the Effect in the Graphic-D27UwulJc2c.ar.vtt
396 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.ar.vtt
396 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.pt-BR.vtt
396 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.ja.vtt
395 Bytes
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.en.vtt
395 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.ar.vtt
395 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.ja.vtt
395 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-47JDwoDUxP8.es.vtt
394 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/04. DF - Choose n Numbers-4XEJJC-vSRw.en.vtt
394 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error-22SXauLJVd4.en.vtt
394 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-HAQ0-Skvzmc.en.vtt
394 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-HAQ0-Skvzmc.en.vtt
394 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/24. Formula for Avg. Abs. Dev.-_c780DW5Wuw.pt-BR.vtt
393 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision-fgg81QJg89s.zh-CN.vtt
393 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.pt-BR.vtt
393 Bytes
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.en-US.vtt
393 Bytes
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.ar.vtt
393 Bytes
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.es-ES.vtt
393 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.pt-BR.vtt
393 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.th.vtt
393 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-YetpTU5SmUg.es.vtt
392 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-U3FUxkm1MxI.zh-CN.vtt
392 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-bUvlDsmmpIo.pt-BR.vtt
392 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.ja.vtt
392 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region-skeY26k1hSs.zh-CN.vtt
391 Bytes
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-Bp6oBbLw8qE.ar.vtt
391 Bytes
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.en.vtt
391 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.pt-BR.vtt
391 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/07. Significance-f0ZWCaOKW1Q.zh-CN.vtt
390 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.ja.vtt
390 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.es-ES.vtt
390 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-gww_oBZTf5k.pt-BR.vtt
389 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size-tX7p7HXlKBQ.zh-CN.vtt
389 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.zh-CN.vtt
389 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.ja.vtt
389 Bytes
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.pt-BR.vtt
389 Bytes
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-9frwavCQvGg.pt-BR.vtt
389 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.ja.vtt
389 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.ja.vtt
389 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.zh-CN.vtt
389 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.es-ES.vtt
389 Bytes
Part 21-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.zh-CN.vtt
389 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post-NtldeU_E4sI.zh-CN.vtt
388 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-AM-d6qA5nnI.ko.vtt
388 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/01. t-Distribution-TC2Ro6pFAqA.zh-CN.vtt
388 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-c7UjSq7Fmr8.ar.vtt
388 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.es-ES.vtt
388 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-obhHCeHpysw.ar.vtt
387 Bytes
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel-yg5c1caIB4E.pt-BR.vtt
387 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.en.vtt
387 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-obhHCeHpysw.ar.vtt
387 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-El5cY2jlzuM.pt-BR.vtt
386 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/14. Andy - SDs Below-xE3Rgjv2Vww.pt-BR.vtt
386 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis-Pk_BMZINZ0k.zh-CN.vtt
386 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/29. Cohen's d-smedG3-3mOE.zh-CN.vtt
386 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-bUvlDsmmpIo.en.vtt
386 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.pt-BR.vtt
386 Bytes
Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-b1V_L3qFIUk.pt-BR.vtt
386 Bytes
Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-ZmDbDYoRxwQ.pt-BR.vtt
386 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/36. Find Values-JP-mQPN9Sl4.zh-CN.vtt
385 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/16. Roll 2 Dice-D4bQbaCAUoE.zh-CN.vtt
385 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment-zWmH6ajoLtE.pt-BR.vtt
385 Bytes
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-8Ygq5dRV0Kk.zh-CN.vtt
385 Bytes
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-nvLhUSSUhiY.ar.vtt
385 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.hr.vtt
384 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/27. Average Squared Deviation-kmVqaJ6n9Vk.zh-CN.vtt
383 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/29. Klout Sampling Distribution (SD)-Qlg5L4TWcZs.pt-BR.vtt
383 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/23. Rent - t-Critical Values-WTmFRvH2AmI.zh-CN.vtt
383 Bytes
Part 05-Module 01-Lesson 05_Data Quality/20. Conclusion-fSwaNltHTio.zh-CN.vtt
383 Bytes
Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-3RuKO3PQWg0.pt-BR.vtt
383 Bytes
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.hr.vtt
383 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.pt-BR.vtt
383 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/35. Keyboards - t-Statistic-aE-ZZw8QVWo.pt-BR.vtt
382 Bytes
Part 11-Module 01-Lesson 07_Regressions/16. Handoff to Katie-M3Nwl_B_bZ8.pt-BR.vtt
382 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-HWW9BNHnPo0.en.vtt
382 Bytes
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.it.vtt
382 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-HWW9BNHnPo0.en.vtt
382 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-7umkXt9U5lE.zh-CN.vtt
381 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-7umkXt9U5lE.zh-CN.vtt
381 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.pt-BR.vtt
381 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/14. Acne Medication - Decision-WzwHLFlkxVA.zh-CN.vtt
380 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision-k1plVVNoyeY.zh-CN.vtt
380 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.zh-CN.vtt
380 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.zh-CN.vtt
380 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-1GuHNqJNY2M.zh-CN.vtt
379 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price-m9IQqYf6ThU.pt-BR.vtt
379 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.pt-BR.vtt
379 Bytes
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.zh-CN.vtt
379 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/08. Probability Mean or = 3-JSlSjQwhIAI.zh-CN.vtt
378 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/21. Visualize P-Value-Za4LLPiE7pI.zh-CN.vtt
378 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error-_h2C0TCvXvA.pt-BR.vtt
378 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-FwaYsmnlLM4.zh-CN.vtt
378 Bytes
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/15. Conclusion-PXBdIBgFTL4.zh-CN.vtt
378 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-FwaYsmnlLM4.zh-CN.vtt
378 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-2wHoLFHnPZs.pt-BR.vtt
377 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.en.vtt
377 Bytes
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/08. Troubleshooting With Appending-KwtjTmDMZGE.pt-BR.vtt
377 Bytes
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.pt-BR.vtt
377 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.pt-BR.vtt
377 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.pt-BR.vtt
376 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.pt-BR.vtt
376 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-ObSZnD336CA.zh-CN.vtt
376 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-QWWq77k-K_0.pt-BR.vtt
376 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.zh-CN.vtt
376 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-QWWq77k-K_0.pt-BR.vtt
376 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-gww_oBZTf5k.es.vtt
375 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/02. Mean of Treated Population-jC4--44m3-I.pt-BR.vtt
375 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/02. Mean of Treated Population-jC4--44m3-I.zh-CN.vtt
375 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean-Hj2HADsZ-rM.pt-BR.vtt
375 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/04. DF - Choose n Numbers-4XEJJC-vSRw.zh-CN.vtt
375 Bytes
Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-QTq9pGMoZAE.pt-BR.vtt
375 Bytes
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.it.vtt
375 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.pt-BR.vtt
375 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-YetpTU5SmUg.zh-CN.vtt
374 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-aALYYSwS7MM.pt-BR.vtt
374 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.ja.vtt
374 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-X_5v9jxuLrQ.zh-CN.vtt
373 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.zh-CN.vtt
373 Bytes
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-uETh8McUAfY.ar.vtt
373 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-QeTWVPi1Evo.pt-BR.vtt
373 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.en.vtt
373 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.ja.vtt
373 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.pt-BR.vtt
373 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-LCrrPfsXaVc.es.vtt
372 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/27. Klout Parameters-CLGwm6tBHlk.zh-CN.vtt
372 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/34. Prone to Misinterpretations-DUVB_GCcado.zh-CN.vtt
372 Bytes
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-9bNGgRojUC0.zh-CN.vtt
372 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-bUvlDsmmpIo.ja.vtt
372 Bytes
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line-O4jFvJWal6s.zh-CN.vtt
372 Bytes
Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-VD14oP-Ue6M.zh-CN.vtt
372 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.it.vtt
372 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs-CtbwhKXSEMs.zh-CN.vtt
371 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/38. Something Fun-S3UsHyKkoww.zh-CN.vtt
371 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-AF07y1oAim0.en.vtt
371 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-aALYYSwS7MM.en.vtt
371 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.zh-CN.vtt
371 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.ja.vtt
371 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-LHLgEooUT4E.en.vtt
370 Bytes
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-FY0DXe0lfrI.pt-BR.vtt
370 Bytes
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.ja.vtt
370 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.en.vtt
370 Bytes
Part 18-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 -dRbjnKOnd0Y.pt-BR.vtt
370 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-9bsmO7cKzPk.zh-CN.vtt
369 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-r2s9INGd-Ls.es.vtt
369 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size-tl4mqs0SqX4.zh-CN.vtt
369 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/16. Mean Number of Shoes-DtdsK8K1OtI.zh-CN.vtt
369 Bytes
Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-9J3IwQFXveI.pt-BR.vtt
369 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.zh-CN.vtt
369 Bytes
Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-eSZ1kr_yZFg.ar.vtt
369 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.zh-CN.vtt
369 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.zh-CN.vtt
369 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/06. Mark Z the Outlier-_UyoOnmH1X8.pt-BR.vtt
368 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/24. Formula for Avg. Abs. Dev.-_c780DW5Wuw.en.vtt
368 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/13. Katie - SDs Below-COHUHzCELK4.zh-CN.vtt
368 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means-7iOMOs56gZE.pt-BR.vtt
368 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/19. Null Hypothesis-ldiOcCeZvx4.en.vtt
368 Bytes
Part 11-Module 01-Lesson 07_Regressions/16. Handoff to Katie-M3Nwl_B_bZ8.en.vtt
368 Bytes
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-FY0DXe0lfrI.en.vtt
368 Bytes
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/08. Troubleshooting With Appending-KwtjTmDMZGE.en.vtt
368 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/31. Good Job!-ZZoeeLpWcmU.pt-BR.vtt
367 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/22. Absolute Deviations-baWB4xYNMIs.pt-BR.vtt
367 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/05. Mean of Each Sample-n7II63ei3LU.pt-BR.vtt
367 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01-9EFRrU4WBs4.pt-BR.vtt
367 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/09. One-Tailed t-Test-3rL-Vk-QIB8.pt-BR.vtt
367 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test-AXYl4jWsA3o.zh-CN.vtt
367 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/16. Mean Number of Shoes-DtdsK8K1OtI.pt-BR.vtt
367 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.zh-CN.vtt
367 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-bhwb2v9rEdI.ar.vtt
367 Bytes
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-cuBxHYSPrkA.pt-BR.vtt
367 Bytes
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-9frwavCQvGg.en.vtt
367 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.es-ES.vtt
367 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.en.vtt
366 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.en.vtt
366 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/18. Deviation from Mean-M43NnIroHws.zh-CN.vtt
366 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/19. Average Deviation-OCLlqMAbxBM.zh-CN.vtt
366 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.pt-BR.vtt
366 Bytes
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-cuBxHYSPrkA.zh-CN.vtt
366 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-HAQ0-Skvzmc.zh-CN.vtt
366 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-maL-S68XvTc.en.vtt
366 Bytes
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel-yg5c1caIB4E.en.vtt
366 Bytes
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.es-ES.vtt
366 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-HAQ0-Skvzmc.zh-CN.vtt
366 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/34. Keyboards - SD of Differences-Ej8yntoeBw0.zh-CN.vtt
365 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/36. Keyboards - t-Critical Values-AP3YFEoi8_M.pt-BR.vtt
365 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic-AeByX89sS4g.zh-CN.vtt
365 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/26. t-Statistic-P4tyKSWJUZc.en.vtt
365 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-LHLgEooUT4E.es.vtt
364 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-RnUTCqsJD68.es.vtt
364 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post-p-ma7uqFNCM.zh-CN.vtt
364 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.zh-CN.vtt
364 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.en.vtt
364 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.zh-CN.vtt
364 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.ar.vtt
364 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.en.vtt
364 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score-JdzOGxmq2jE.zh-CN.vtt
363 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI-S8sB8ph_bQM.pt-BR.vtt
363 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.pt-BR.vtt
363 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.es.vtt
362 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.es.vtt
362 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.zh-CN.vtt
362 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.es.vtt
362 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.es.vtt
362 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.zh-CN.vtt
362 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/12. Generalize CI-HgumODgJSdQ.pt-BR.vtt
362 Bytes
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-GwzB76HYlFE.zh-CN.vtt
362 Bytes
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.ar.vtt
362 Bytes
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-2FQu07aKLwg.en.vtt
362 Bytes
Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.pt-BR.vtt
362 Bytes
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/08. Troubleshooting With Appending-KwtjTmDMZGE.zh-CN.vtt
362 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.pt-BR.vtt
362 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.zh-CN.vtt
362 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/17. Evidence to Reject the Null-a5RRRMRZl8I.pt-BR.vtt
361 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/03. Meal Prices-f_WdPsfeLDs.pt-BR.vtt
361 Bytes
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-FY0DXe0lfrI.zh-CN.vtt
361 Bytes
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.zh-CN.vtt
361 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI-S8sB8ph_bQM.en.vtt
360 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.en.vtt
360 Bytes
Part 11-Module 01-Lesson 03_SVM/09. Handoff to Katie-GkqOdgZnkig.ja.vtt
360 Bytes
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-QsncWsyboFk.ar.vtt
360 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.pt-BR.vtt
360 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.es-ES.vtt
360 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-dXS9vjgXyg4.zh-CN.vtt
359 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.ar.vtt
359 Bytes
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.ar.vtt
359 Bytes
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.th.vtt
359 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.it.vtt
359 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/19. Standard Error for Avg of 5 Dice-18DMT9dnLPE.pt-BR.vtt
358 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/29. Klout Sampling Distribution (SD)-Qlg5L4TWcZs.en.vtt
358 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/24. t-Statistic-KmEfiWATLUI.en.vtt
358 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.es-ES.vtt
358 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.en.vtt
358 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-MPPgcjHAfkA.en.vtt
357 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-RnUTCqsJD68.pt-BR.vtt
357 Bytes
Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-AF07y1oAim0.zh-CN.vtt
357 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.ar.vtt
357 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.ja.vtt
357 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.ja.vtt
357 Bytes
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-T-dTpFd7EO0.ar.vtt
357 Bytes
Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-bAZJT4xHiXM.ar.vtt
357 Bytes
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.ja.vtt
357 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.es-ES.vtt
357 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.en.vtt
357 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.es-ES.vtt
357 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.pt-BR.vtt
356 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.pt-BR.vtt
356 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning-DKxww0fCCAA.en.vtt
356 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-2StCBxTOoK0.ar.vtt
356 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.ar.vtt
356 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.zh-CN.vtt
356 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.es-ES.vtt
356 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.pt-BR.vtt
356 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/34. Does Low Probability = Causation-KaBa9N2TdnQ.en.vtt
355 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-AM-d6qA5nnI.pt-BR.vtt
355 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.ar.vtt
355 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.pt-BR.vtt
355 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-T7rdBFQQ0Fw.zh-CN.vtt
355 Bytes
Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-9J3IwQFXveI.en.vtt
355 Bytes
Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-9J3IwQFXveI.zh-CN.vtt
355 Bytes
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-2FQu07aKLwg.pt-BR.vtt
355 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.zh-CN.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.es-ES.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-MPPgcjHAfkA.pt-BR.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment-zWmH6ajoLtE.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis-KFSiwhv4q7s.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-CMIM_Ocu8vg.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.th.vtt
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Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.en.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-CMIM_Ocu8vg.pt-BR.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample-I487nBkmUoM.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/18. Better Sample-I487nBkmUoM.pt-BR.vtt
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Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-qhhrjvLF8H8.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/31. Good Job!-ZZoeeLpWcmU.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/20. Standard Error When n Increases-mbCavcKeZqo.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean-potr9cTBlxI.zh-CN.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/23. Pooled Variance Sum of Squares-c0lWwW1Z9Ac.zh-CN.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/26. t-Statistic-KvaW3rL7u4k.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.ja.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-m2waMNsE1sU.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/04. Total Number of Samples-s0J73PTr9Rw.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.zh-CN.vtt
352 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bEAaNv-CBQ4.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-HWW9BNHnPo0.zh-CN.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bEAaNv-CBQ4.ar.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-HWW9BNHnPo0.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely-9jGIDxEr9A4.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely-9jGIDxEr9A4.pt-BR.vtt
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-jP1KfLaTtpU.zh-CN.vtt
351 Bytes
Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-QTq9pGMoZAE.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.ja.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-AjI84ujXBHk.ja.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.en.vtt
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-jP1KfLaTtpU.zh-CN.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/01. Compare Sample Means-l9Sy4qoLHVo.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size-_Oh9-SQDtYg.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.ja.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-CMIM_Ocu8vg.en.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.es-ES.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.ja.vtt
350 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-CMIM_Ocu8vg.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-6pxpT3bZI54.es.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/18. Finches - Find t-Statistic-nBqsiW5r-98.zh-CN.vtt
349 Bytes
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-pt_S3HwE5GY.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/43. Calculating the Lie Factor-U3ZnXlDS5No.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-QeTWVPi1Evo.en-US.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.en.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/12. Two-Tailed Probability-68_OkDcn6dI.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/33. Keyboards Point Estimate for Difference-Rw3QBEnIlJY.zh-CN.vtt
348 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error-sYOGafbS30Q.en.vtt
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Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-pt_S3HwE5GY.en.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-LoLj_Ecohew.en.vtt
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Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.es-ES.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.es-ES.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-LCrrPfsXaVc.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/24. Formula for Avg. Abs. Dev.-_c780DW5Wuw.zh-CN.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean-Hj2HADsZ-rM.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.en.vtt
347 Bytes
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-LoLj_Ecohew.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-El5cY2jlzuM.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/06. Mark Z the Outlier-_UyoOnmH1X8.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/33. What Happened-6mxt0l8IpOM.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/15. Finches-Y6qz1XqyO9w.pt-BR.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference-yu70KwoztEg.pt-BR.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-QWWq77k-K_0.en.vtt
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Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-QeTWVPi1Evo.en.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-QWWq77k-K_0.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/15. Finches-Y6qz1XqyO9w.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM-jHzmtwd-xTs.pt-BR.vtt
345 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values-coHA_ziMiws.zh-CN.vtt
345 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-aUc0FKD4834.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.ja.vtt
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Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.ar.vtt
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Part 13-Module 01-Lesson 04_Design Principles/37. Chartjunk Qualities-R6Sggtsz5LM.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.ja.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.en.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.en.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-2wHoLFHnPZs.en.vtt
344 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price--P5lMGuVA6U.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-XN1eS7boCNg.pt-BR.vtt
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-b1V_L3qFIUk.en.vtt
344 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-XN1eS7boCNg.pt-BR.vtt
344 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/09. One-Tailed t-Test-3rL-Vk-QIB8.en.vtt
343 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/24. Calculate Pooled Variance-evwkqnO9BHY.en.vtt
343 Bytes
Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-ZmDbDYoRxwQ.en.vtt
343 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-maL-S68XvTc.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price--P5lMGuVA6U.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.zh-CN.vtt
342 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-maL-S68XvTc.pt-BR.vtt
342 Bytes
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.th.vtt
342 Bytes
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.en.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.ar.vtt
342 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-VkZ-W3kh9PA.en.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/14. Andy - SDs Below-xE3Rgjv2Vww.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/19. Standard Error for Avg of 5 Dice-RQ_AHYQTSDA.zh-CN.vtt
341 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/25. Rent - Decision-edm9jPvzeAc.zh-CN.vtt
341 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis-kW_p0VHNEPM.zh-CN.vtt
341 Bytes
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-Bp6oBbLw8qE.pt-BR.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-oTAhEKrWq2g.pt-BR.vtt
341 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.en.vtt
341 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.it.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.ar.vtt
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Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-qhhrjvLF8H8.es.vtt
340 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/09. Continuous Distribution-IncW1Q44jMk.en.vtt
340 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/23. Convert to Z-Score-tBlCLuL2tFc.pt-BR.vtt
340 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/36. Keyboards - t-Critical Values-AP3YFEoi8_M.en.vtt
340 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-s_-I8mbrfw0.ar.vtt
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Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-wnIQ6fCVD40.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/43. Calculating the Lie Factor-U3ZnXlDS5No.pt-BR.vtt
340 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.en.vtt
340 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/31. Good Job!-ZZoeeLpWcmU.zh-CN.vtt
339 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/19. Between 10 and 16-lMm_BrpheLM.en.vtt
339 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.ja.vtt
339 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.en.vtt
339 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-aALYYSwS7MM.zh-CN.vtt
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Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-Z2bA98cBS4Q.ar.vtt
339 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.en.vtt
339 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.th.vtt
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Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/01. 7. Ode to n-c2Das5kJFe4.pt-BR.vtt
338 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-47JDwoDUxP8.zh-CN.vtt
338 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference-yu70KwoztEg.en.vtt
338 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.it.vtt
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Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.es.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.es.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/04. DF - Choose n Numbers-_Ns0gk4T7eo.pt-BR.vtt
337 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/29. Rent - Margin of Error-nHF7LgYaZnE.zh-CN.vtt
337 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-oNTklG8dh-0.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.en.vtt
337 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.es-ES.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.en.vtt
337 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.pt-BR.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-m2waMNsE1sU.zh-CN.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values-e2C4tEKNtqs.zh-CN.vtt
336 Bytes
Part 09-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-2StCBxTOoK0.ja.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/22. Absolute Deviations-baWB4xYNMIs.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.pt-BR.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.zh-CN.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-XN1eS7boCNg.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.pt-BR.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-XN1eS7boCNg.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-El5cY2jlzuM.es.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-6pxpT3bZI54.en.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01-6RNfHbEL4ZQ.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error-22SXauLJVd4.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.ja.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.ar.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-gww_oBZTf5k.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/09. What We Need to Compare the Means-SAjAfP-Y9O8.pt-BR.vtt
333 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean-dsje3j3gn_s.pt-BR.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-AM-d6qA5nnI.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-AM-d6qA5nnI.zh-CN.vtt
333 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01-9EFRrU4WBs4.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/03. Meal Prices-f_WdPsfeLDs.en.vtt
333 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-QWWq77k-K_0.zh-CN.vtt
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Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-oTAhEKrWq2g.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.es-ES.vtt
333 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-QWWq77k-K_0.zh-CN.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error-_h2C0TCvXvA.en.vtt
332 Bytes
Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-bUvlDsmmpIo.zh-CN.vtt
332 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price--P5lMGuVA6U.en.vtt
332 Bytes
Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-xPDk70gKkjk.en.vtt
332 Bytes
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-uC1Xwc7warg.zh-CN.vtt
332 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.es-ES.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.ja.vtt
332 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.pt-BR.vtt
332 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-LHLgEooUT4E.zh-CN.vtt
331 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/35. Keyboards - t-Statistic-aE-ZZw8QVWo.en.vtt
331 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis-kW_p0VHNEPM.pt-BR.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/21. t-Critical-9-yTPJl_DIw.zh-CN.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.zh-CN.vtt
331 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.en.vtt
331 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.en.vtt
331 Bytes
Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-xPDk70gKkjk.pt-BR.vtt
331 Bytes
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.pt-BR.vtt
331 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.ja.vtt
331 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/27. Rent - CI-C8I9uVBKems.pt-BR.vtt
330 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-RnUTCqsJD68.en.vtt
329 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/12. Two-Tailed Probability-68_OkDcn6dI.zh-CN.vtt
329 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.ja.vtt
329 Bytes
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel-yg5c1caIB4E.zh-CN.vtt
329 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.es-ES.vtt
329 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.pt-BR.vtt
329 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/04. Probability Greater-5DZTwMn7GAY.zh-CN.vtt
328 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5-CHHhDWRG49A.pt-BR.vtt
328 Bytes
Part 11-Module 01-Lesson 07_Regressions/16. Handoff to Katie-M3Nwl_B_bZ8.zh-CN.vtt
328 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-r2s9INGd-Ls.en-US.vtt
327 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/20. Standard Error When n Increases-mbCavcKeZqo.en.vtt
327 Bytes
Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-QTq9pGMoZAE.zh-CN.vtt
327 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.zh-CN.vtt
327 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-k63Why0c1KU.ar.vtt
327 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.es-ES.vtt
327 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.ja.vtt
327 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-VkZ-W3kh9PA.es.vtt
326 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error-ZU9uRiqLgxA.zh-CN.vtt
326 Bytes
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-uC1Xwc7warg.pt-BR.vtt
326 Bytes
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.pt-BR.vtt
326 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-TWGqylKdGWs.ar.vtt
326 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.ja.vtt
326 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.ja.vtt
326 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-TWGqylKdGWs.ar.vtt
326 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.ja.vtt
325 Bytes
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.en.vtt
325 Bytes
Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.en.vtt
325 Bytes
Part 13-Module 01-Lesson 04_Design Principles/43. Calculating the Lie Factor-U3ZnXlDS5No.zh-CN.vtt
325 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.en.vtt
325 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.ar.vtt
325 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.zh-CN.vtt
325 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-m2waMNsE1sU.pt-BR.vtt
324 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/23. Convert to Z-Score-tBlCLuL2tFc.en.vtt
324 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error-ksf2wklgpZ8.pt-BR.vtt
324 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.pt-BR.vtt
324 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.it.vtt
324 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-r2s9INGd-Ls.en.vtt
323 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment-zWmH6ajoLtE.zh-CN.vtt
323 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic-LDdm06-FHYI.zh-CN.vtt
323 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-ijy0n1EjY0M.ar.vtt
323 Bytes
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.zh-CN.vtt
323 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.ja.vtt
323 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-MPPgcjHAfkA.es.vtt
322 Bytes
Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/01. 7. Ode to n-c2Das5kJFe4.es.vtt
322 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/11. Generalize Point Estimate-JveZxEnq9bI.pt-BR.vtt
322 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/04. DF - Choose n Numbers-_Ns0gk4T7eo.en.vtt
322 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.en.vtt
322 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.zh-CN.vtt
321 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.zh-CN.vtt
321 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-2wHoLFHnPZs.es.vtt
321 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/19. Standard Error for Avg of 5 Dice-18DMT9dnLPE.en.vtt
321 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250-mCp7zkPv6o4.pt-BR.vtt
321 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size-_Oh9-SQDtYg.en.vtt
321 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-AjI84ujXBHk.en.vtt
321 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.en-US.vtt
321 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/17. Evidence to Reject the Null-a5RRRMRZl8I.en.vtt
320 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/17. Finches - Mean and s-nInJKeAmAeY.pt-BR.vtt
320 Bytes
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.en.vtt
320 Bytes
Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-3RuKO3PQWg0.en.vtt
320 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.zh-CN.vtt
320 Bytes
Part 18-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 -dRbjnKOnd0Y.en.vtt
320 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/09. What We Need to Compare the Means-SAjAfP-Y9O8.en.vtt
319 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/17. Finches - Mean and s-nInJKeAmAeY.en.vtt
319 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis-KFSiwhv4q7s.pt-BR.vtt
319 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.zh-CN.vtt
319 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.zh-CN.vtt
319 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-XN1eS7boCNg.en.vtt
319 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-r8stm2et_hI.ar.vtt
319 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/18. Averaging Locations-bQQSqytU_r0.ar.vtt
319 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.hr.vtt
319 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.ar.vtt
319 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-XN1eS7boCNg.en.vtt
319 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-r8stm2et_hI.ar.vtt
319 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.zh-CN.vtt
318 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.zh-CN.vtt
318 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.pt-BR.vtt
318 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.en.vtt
318 Bytes
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.es-ES.vtt
318 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-gww_oBZTf5k.zh-CN.vtt
317 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-MPPgcjHAfkA.zh-CN.vtt
317 Bytes
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-qhhrjvLF8H8.zh-CN.vtt
317 Bytes
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-Or9KvEd1flY.ar.vtt
317 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-0E08XPKeRNg.pt-BR.vtt
317 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.en.vtt
317 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.pt-BR.vtt
317 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-s9dHF4MMGx0.es.vtt
316 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means-7iOMOs56gZE.en.vtt
316 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.ja.vtt
316 Bytes
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-wnIQ6fCVD40.en.vtt
316 Bytes
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.zh-CN.vtt
316 Bytes
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-9frwavCQvGg.zh-CN.vtt
316 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.zh-CN.vtt
316 Bytes
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-Bp6oBbLw8qE.en.vtt
315 Bytes
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.zh-CN.vtt
315 Bytes
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-nvLhUSSUhiY.en.vtt
315 Bytes
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.it.vtt
315 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.ja.vtt
315 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.ar.vtt
315 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/06. Mark Z the Outlier-_UyoOnmH1X8.zh-CN.vtt
314 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.ja.vtt
314 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-V0FNwMKhIVM.ja.vtt
314 Bytes
Part 13-Module 01-Lesson 04_Design Principles/42. Size of the Effect in the Graphic-D27UwulJc2c.pt-BR.vtt
314 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.it.vtt
314 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.zh-CN.vtt
314 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/26. t-Statistic-KvaW3rL7u4k.en.vtt
313 Bytes
Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-b1V_L3qFIUk.zh-CN.vtt
313 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-0E08XPKeRNg.en.vtt
313 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.en.vtt
313 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-s9dHF4MMGx0.pt-BR.vtt
312 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/25. Squared Deviations-oA37LlWNYCw.pt-BR.vtt
312 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/34. Does Low Probability = Causation-KaBa9N2TdnQ.zh-CN.vtt
312 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-V0FNwMKhIVM.zh-CN.vtt
312 Bytes
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-Bp6oBbLw8qE.zh-CN.vtt
312 Bytes
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-uC1Xwc7warg.en.vtt
312 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.ar.vtt
312 Bytes
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.hr.vtt
312 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.zh-CN.vtt
311 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-2StCBxTOoK0.pt-BR.vtt
311 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.it.vtt
311 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-s9dHF4MMGx0.en.vtt
310 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/31. Calculate SD-E1iDHrumLoo.en.vtt
310 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning-DKxww0fCCAA.zh-CN.vtt
310 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.en.vtt
310 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.en.vtt
310 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.ja.vtt
310 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample-I487nBkmUoM.en.vtt
309 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/18. Better Sample-I487nBkmUoM.en.vtt
309 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-h9IP6OuMQrk.es.vtt
309 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5-CHHhDWRG49A.en.vtt
309 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-t4qaavAslSw.ar.vtt
309 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bEAaNv-CBQ4.pt-BR.vtt
309 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.zh-CN.vtt
309 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bEAaNv-CBQ4.pt-BR.vtt
309 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.zh-CN.vtt
308 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.zh-CN.vtt
308 Bytes
Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/01. 7. Ode to n-c2Das5kJFe4.en.vtt
308 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01-6RNfHbEL4ZQ.zh-CN.vtt
308 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/36. Keyboards - t-Critical Values-AP3YFEoi8_M.zh-CN.vtt
308 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis-KFSiwhv4q7s.zh-CN.vtt
308 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-W96zaGEma7o.ar.vtt
308 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-AjI84ujXBHk.zh-CN.vtt
308 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.it.vtt
308 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/33. What Happened-6mxt0l8IpOM.en.vtt
307 Bytes
Part 11-Module 01-Lesson 03_SVM/09. Handoff to Katie-GkqOdgZnkig.pt-BR.vtt
307 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-obhHCeHpysw.pt-BR.vtt
307 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.it.vtt
307 Bytes
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.en.vtt
307 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.zh-CN.vtt
307 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-obhHCeHpysw.pt-BR.vtt
307 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-r2s9INGd-Ls.zh-CN.vtt
306 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.zh-CN.vtt
306 Bytes
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-nvLhUSSUhiY.pt-BR.vtt
306 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-J6RyUyWxrM4.ar.vtt
306 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-2cUiqlbt-hc.en.vtt
306 Bytes
Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-eSZ1kr_yZFg.pt-BR.vtt
306 Bytes
Part 13-Module 01-Lesson 04_Design Principles/37. Chartjunk Qualities-R6Sggtsz5LM.pt-BR.vtt
306 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-2cUiqlbt-hc.en.vtt
306 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/12. Generalize CI-HgumODgJSdQ.en.vtt
305 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/27. Statistically Significant-VXgMxs0tiBw.en.vtt
305 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/32. Compute CI-Adzhg-M3Pvk.en.vtt
305 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-AjI84ujXBHk.pt-BR.vtt
305 Bytes
Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.zh-CN.vtt
305 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-2cUiqlbt-hc.pt-BR.vtt
305 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-oTAhEKrWq2g.zh-CN.vtt
305 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.ja.vtt
305 Bytes
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.hr.vtt
305 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.ja.vtt
305 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.th.vtt
305 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.zh-CN.vtt
305 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-2cUiqlbt-hc.pt-BR.vtt
305 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-h9IP6OuMQrk.pt-BR.vtt
304 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/14. Andy - SDs Below-xE3Rgjv2Vww.zh-CN.vtt
304 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/30. Sampling Distribution Shape-UMEckGyua6o.pt-BR.vtt
304 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean-dsje3j3gn_s.en.vtt
304 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01-9EFRrU4WBs4.zh-CN.vtt
304 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/04. DF - Choose n Numbers-_Ns0gk4T7eo.zh-CN.vtt
304 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI-S8sB8ph_bQM.zh-CN.vtt
304 Bytes
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-IC-fo_A0PxQ.ar.vtt
304 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.ja.vtt
304 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.zh-CN.vtt
304 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.ja.vtt
304 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-6pxpT3bZI54.zh-CN.vtt
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Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-m2waMNsE1sU.es.vtt
303 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference-eTNZnE_O_RM.pt-BR.vtt
303 Bytes
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-2FQu07aKLwg.zh-CN.vtt
303 Bytes
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.ar.vtt
303 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.ar.vtt
303 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.zh-CN.vtt
303 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.zh-CN.vtt
303 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-El5cY2jlzuM.zh-CN.vtt
302 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-2wHoLFHnPZs.zh-CN.vtt
302 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/09. Continuous Distribution-IncW1Q44jMk.zh-CN.vtt
302 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/19. Between 10 and 16-lMm_BrpheLM.zh-CN.vtt
302 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size-_Oh9-SQDtYg.zh-CN.vtt
302 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price-m9IQqYf6ThU.en.vtt
302 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/26. t-Statistic-P4tyKSWJUZc.zh-CN.vtt
302 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-nNna_SLlIT8.ar.vtt
302 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-j1vFBL3khh0.ar.vtt
302 Bytes
Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-bAZJT4xHiXM.pt-BR.vtt
302 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bEAaNv-CBQ4.en.vtt
302 Bytes
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.ar.vtt
302 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.zh-CN.vtt
302 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.ar.vtt
302 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.ja.vtt
302 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bEAaNv-CBQ4.en.vtt
302 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-RnUTCqsJD68.zh-CN.vtt
301 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM-jHzmtwd-xTs.en.vtt
301 Bytes
Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.ar.vtt
301 Bytes
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.ja.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.ja.vtt
301 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.es-ES.vtt
301 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/22. Absolute Deviations-baWB4xYNMIs.zh-CN.vtt
300 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means-TpsMv7isR6U.pt-BR.vtt
300 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/17. Evidence to Reject the Null-a5RRRMRZl8I.zh-CN.vtt
300 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.ja.vtt
300 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.ja.vtt
300 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-FBRK-XwPC54.ar.vtt
299 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-DzyOcsBIncA.pt-BR.vtt
299 Bytes
Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-FpQm_dYA9LM.zh-CN.vtt
299 Bytes
Part 13-Module 01-Lesson 04_Design Principles/42. Size of the Effect in the Graphic-D27UwulJc2c.en.vtt
299 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.th.vtt
299 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-LCrrPfsXaVc.zh-CN.vtt
298 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210-OBxWYhF4VdI.en.vtt
298 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/11. Generalize Point Estimate-JveZxEnq9bI.en.vtt
298 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error-cLyzI4feDEw.pt-BR.vtt
298 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/03. Meal Prices-f_WdPsfeLDs.zh-CN.vtt
298 Bytes
Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-QfIgUDXPhi8.ar.vtt
298 Bytes
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.en.vtt
298 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.ja.vtt
298 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.zh-CN.vtt
298 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error-cLyzI4feDEw.en.vtt
297 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values-CRlOfleyRNY.en.vtt
297 Bytes
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.ja.vtt
297 Bytes
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-t4qaavAslSw.ja.vtt
297 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-c7UjSq7Fmr8.ja.vtt
297 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.zh-CN.vtt
297 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/14. Andy - SDs Below-4VKOJowrOoU.pt-BR.vtt
296 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.en.vtt
296 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.ja.vtt
296 Bytes
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-NixhPePGk-s.ar.vtt
296 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.zh-CN.vtt
296 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.ja.vtt
296 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/20. SD of Standardized Distribution-0JZyJ5_T858.en.vtt
295 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.zh-CN.vtt
295 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample-I487nBkmUoM.zh-CN.vtt
294 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/18. Better Sample-I487nBkmUoM.zh-CN.vtt
294 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-mFm0FfWHlXw.es.vtt
294 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/31. Calculate SD-E1iDHrumLoo.pt-BR.vtt
294 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean-p3e965clFyU.pt-BR.vtt
294 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/14. Acne Medication - Decision-GCk9hNs1uxY.pt-BR.vtt
294 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-CMIM_Ocu8vg.zh-CN.vtt
294 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-CMIM_Ocu8vg.zh-CN.vtt
294 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200--scGDVG9KJ8.pt-BR.vtt
293 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/05. Mean of Each Sample-n7II63ei3LU.en.vtt
293 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250-mCp7zkPv6o4.en.vtt
293 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.pt-BR.vtt
293 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.ja.vtt
293 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.zh-CN.vtt
293 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.pt-BR.vtt
293 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.pt-BR.vtt
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.pt-BR.vtt
292 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean-dsje3j3gn_s.zh-CN.vtt
292 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.zh-CN.vtt
292 Bytes
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-QsncWsyboFk.en.vtt
292 Bytes
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-QsncWsyboFk.pt-BR.vtt
292 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-obhHCeHpysw.en.vtt
292 Bytes
Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-eSZ1kr_yZFg.en.vtt
292 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-obhHCeHpysw.en.vtt
292 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-VkZ-W3kh9PA.zh-CN.vtt
291 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/23. Critical Values 0.05-KQZnIM7YWAg.en.vtt
291 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/23. Critical Values 0.05-KQZnIM7YWAg.pt-BR.vtt
291 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/15. Finches-Y6qz1XqyO9w.zh-CN.vtt
291 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/27. Rent - CI-C8I9uVBKems.en.vtt
291 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price-mlNMENDGqtk.en.vtt
291 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.ja.vtt
291 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.pt-BR.vtt
291 Bytes
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-wnIQ6fCVD40.zh-CN.vtt
291 Bytes
Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-xPDk70gKkjk.zh-CN.vtt
291 Bytes
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-yB866_TLZB8.ar.vtt
291 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.zh-CN.vtt
291 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.hr.vtt
291 Bytes
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.it.vtt
291 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.pt-BR.vtt
291 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.zh-CN.vtt
291 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median-zQzgB8KovNU.es.vtt
290 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/19. Null Hypothesis-ldiOcCeZvx4.pt-BR.vtt
290 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/09. One-Tailed t-Test-3rL-Vk-QIB8.zh-CN.vtt
290 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-V0FNwMKhIVM.en.vtt
290 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-DzyOcsBIncA.en.vtt
290 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.pt-BR.vtt
289 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-c7UjSq7Fmr8.en.vtt
289 Bytes
Part 13-Module 01-Lesson 04_Design Principles/42. Size of the Effect in the Graphic-nahhIlT8uSs.ar.vtt
289 Bytes
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.hr.vtt
289 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.it.vtt
289 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200--scGDVG9KJ8.en.vtt
288 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/19. Null Hypothesis-ldiOcCeZvx4.zh-CN.vtt
288 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-2cUiqlbt-hc.zh-CN.vtt
288 Bytes
Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-ZmDbDYoRxwQ.zh-CN.vtt
288 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-2cUiqlbt-hc.zh-CN.vtt
288 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-U74HWk-E_jg.pt-BR.vtt
287 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210-OBxWYhF4VdI.pt-BR.vtt
287 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/20. Standard Error When n Increases-mbCavcKeZqo.zh-CN.vtt
287 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test--Ecdsb39FnM.pt-BR.vtt
287 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic-A8xSEFaFuBc.pt-BR.vtt
287 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-2StCBxTOoK0.en.vtt
287 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.zh-CN.vtt
287 Bytes
Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-3RuKO3PQWg0.zh-CN.vtt
287 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/09. What We Need to Compare the Means-SAjAfP-Y9O8.zh-CN.vtt
286 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-0r9S6UNDRu8.ko.vtt
286 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error-_h2C0TCvXvA.zh-CN.vtt
286 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.en.vtt
286 Bytes
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-uETh8McUAfY.zh-CN.vtt
286 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.ar.vtt
286 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210-OBxWYhF4VdI.zh-CN.vtt
285 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210-pX6RbiR-4PM.pt-BR.vtt
285 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.ja.vtt
285 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.zh-CN.vtt
285 Bytes
Part 11-Module 01-Lesson 03_SVM/09. Handoff to Katie-GkqOdgZnkig.en.vtt
285 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.en.vtt
285 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-PDqyWzZCVBY.ar.vtt
285 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-QeTWVPi1Evo.zh-CN.vtt
285 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.pt-BR.vtt
285 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-sPqs7DoBkXQ.ar.vtt
284 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.pt-BR.vtt
284 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means-7iOMOs56gZE.zh-CN.vtt
283 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-nNna_SLlIT8.ja.vtt
283 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-yWPbe8onCeA.ar.vtt
283 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bEAaNv-CBQ4.zh-CN.vtt
283 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.ar.vtt
283 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bEAaNv-CBQ4.zh-CN.vtt
283 Bytes
Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/01. 7. Ode to n-c2Das5kJFe4.zh-CN.vtt
282 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/19. Standard Error for Avg of 5 Dice-18DMT9dnLPE.zh-CN.vtt
282 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/27. Statistically Significant-VXgMxs0tiBw.pt-BR.vtt
282 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.en.vtt
282 Bytes
Part 11-Module 01-Lesson 03_SVM/09. Handoff to Katie-GkqOdgZnkig.zh-CN.vtt
282 Bytes
Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete-4yapJV56YoM.ar.vtt
282 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron-MetxO9LDp-I.ar.vtt
282 Bytes
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-uETh8McUAfY.en.vtt
282 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.zh-CN.vtt
282 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200-Ss00WF8qXHk.pt-BR.vtt
281 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-UnkrtPPx9-c.ar.vtt
281 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.ar.vtt
281 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-s_-I8mbrfw0.ja.vtt
281 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-r8stm2et_hI.pt-BR.vtt
281 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.en.vtt
281 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.es-ES.vtt
281 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-r8stm2et_hI.pt-BR.vtt
281 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely-9jGIDxEr9A4.zh-CN.vtt
280 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/17. Evidence to Reject the Null-BHRLT1tJXHU.pt-BR.vtt
280 Bytes
Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-0E08XPKeRNg.zh-CN.vtt
280 Bytes
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.zh-CN.vtt
280 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-mFm0FfWHlXw.pt-BR.vtt
279 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/20. SD of Standardized Distribution-0JZyJ5_T858.pt-BR.vtt
279 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/29. Klout Sampling Distribution (SD)-Qlg5L4TWcZs.zh-CN.vtt
279 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/30. Rent - Increase n-Z3Fl0WPJFoA.pt-BR.vtt
279 Bytes
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.ja.vtt
279 Bytes
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-uETh8McUAfY.pt-BR.vtt
279 Bytes
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-LoLj_Ecohew.zh-CN.vtt
279 Bytes
Part 13-Module 01-Lesson 04_Design Principles/37. Chartjunk Qualities-R6Sggtsz5LM.en.vtt
279 Bytes
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.ar.vtt
279 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.en.vtt
279 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median-zQzgB8KovNU.pt-BR.vtt
278 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.ar.vtt
278 Bytes
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.ar.vtt
278 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-oNTklG8dh-0.ja.vtt
277 Bytes
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-nvLhUSSUhiY.zh-CN.vtt
277 Bytes
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-QsncWsyboFk.zh-CN.vtt
277 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-r8stm2et_hI.en.vtt
277 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.zh-CN.vtt
277 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-r8stm2et_hI.en.vtt
277 Bytes
Part 18-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 -dRbjnKOnd0Y.zh-CN.vtt
277 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean-Hj2HADsZ-rM.zh-CN.vtt
276 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price-mlNMENDGqtk.pt-BR.vtt
276 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-c7UjSq7Fmr8.pt-BR.vtt
276 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.pt-BR.vtt
276 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-s9dHF4MMGx0.zh-CN.vtt
275 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/26. Rent - Cohen's d-k7eajev401c.pt-BR.vtt
275 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.zh-CN.vtt
275 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.pt-BR.vtt
274 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.ar.vtt
274 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/13. Two-Tailed Critical Values 0.01-Kb_OuJuCFH0.pt-BR.vtt
273 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/32. Compute CI-Adzhg-M3Pvk.zh-CN.vtt
273 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price-MZyle39D5Ks.ar.vtt
273 Bytes
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.en.vtt
273 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-V0FNwMKhIVM.pt-BR.vtt
273 Bytes
Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-bAZJT4xHiXM.en.vtt
273 Bytes
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Tidiness-LSdhieL7nXU.pt-BR.vtt
273 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/33. What Happened-6mxt0l8IpOM.zh-CN.vtt
272 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/17. Finches - Mean and s-nInJKeAmAeY.zh-CN.vtt
272 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-bhwb2v9rEdI.pt-BR.vtt
272 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-j1vFBL3khh0.pt-BR.vtt
272 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.es-ES.vtt
272 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/31. Calculate SD-E1iDHrumLoo.zh-CN.vtt
271 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-GtiLFC7EgFE.ar.vtt
271 Bytes
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-yB866_TLZB8.zh-CN.vtt
271 Bytes
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.pt-BR.vtt
271 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-t4qaavAslSw.pt-BR.vtt
270 Bytes
Part 13-Module 01-Lesson 04_Design Principles/37. Chartjunk Qualities-R6Sggtsz5LM.zh-CN.vtt
270 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio-R2a1wC3k0JM.pt-BR.vtt
269 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic-HruTS4wHpVQ.pt-BR.vtt
269 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM-jHzmtwd-xTs.zh-CN.vtt
269 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.pt-BR.vtt
269 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price-m9IQqYf6ThU.zh-CN.vtt
268 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values-CRlOfleyRNY.pt-BR.vtt
268 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/24. Calculate Pooled Variance-evwkqnO9BHY.zh-CN.vtt
268 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.zh-CN.vtt
268 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.en.vtt
268 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-RF_DpOg--PY.es.vtt
267 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-U74HWk-E_jg.en.vtt
267 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5-CHHhDWRG49A.zh-CN.vtt
267 Bytes
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.th.vtt
267 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-nNna_SLlIT8.zh-CN.vtt
266 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.pt-BR.vtt
266 Bytes
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Tidiness-LSdhieL7nXU.ar.vtt
266 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-0r9S6UNDRu8.pt-BR.vtt
265 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/27. Rent - CI-C8I9uVBKems.zh-CN.vtt
265 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.en.vtt
265 Bytes
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8TqVHRan4Fo.ar.vtt
265 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-WmnGwUCW-Yc.ar.vtt
265 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-8fM13xqU2a8.ar.vtt
265 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.ar.vtt
265 Bytes
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.pt-BR.vtt
265 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.ar.vtt
265 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-8fM13xqU2a8.ar.vtt
265 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less-1PkuYCWwc_g.pt-BR.vtt
264 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/33. Probability of Obtaining Mean-wQ3iwH9b10w.pt-BR.vtt
264 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-bhwb2v9rEdI.zh-CN.vtt
264 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.zh-CN.vtt
264 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-TWGqylKdGWs.pt-BR.vtt
264 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.ja.vtt
264 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-TWGqylKdGWs.pt-BR.vtt
264 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price--9CHGW25yMg.ja.vtt
263 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.ar.vtt
263 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.zh-CN.vtt
263 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.en.vtt
263 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.en.vtt
263 Bytes
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-pt_S3HwE5GY.zh-CN.vtt
263 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/24. t-Statistic-KmEfiWATLUI.zh-CN.vtt
262 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error-sYOGafbS30Q.zh-CN.vtt
262 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price--9CHGW25yMg.ar.vtt
262 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-t4qaavAslSw.en.vtt
262 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.ja.vtt
262 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.pt-BR.vtt
262 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-U74HWk-E_jg.es.vtt
261 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-h9IP6OuMQrk.en.vtt
261 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/12. Generalize CI-HgumODgJSdQ.zh-CN.vtt
261 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/23. Critical Values 0.05-KQZnIM7YWAg.zh-CN.vtt
261 Bytes
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.pt-BR.vtt
261 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-bhwb2v9rEdI.ja.vtt
261 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-s_-I8mbrfw0.pt-BR.vtt
261 Bytes
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.ja.vtt
261 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250-mCp7zkPv6o4.zh-CN.vtt
260 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference-yu70KwoztEg.zh-CN.vtt
260 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values-CRlOfleyRNY.zh-CN.vtt
260 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.zh-CN.vtt
260 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-bhwb2v9rEdI.en.vtt
260 Bytes
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.en.vtt
260 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.pt-BR.vtt
260 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.ja.vtt
260 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.es-ES.vtt
260 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means-TpsMv7isR6U.en.vtt
259 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test--Ecdsb39FnM.zh-CN.vtt
259 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-c7UjSq7Fmr8.zh-CN.vtt
259 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/25. Squared Deviations-oA37LlWNYCw.en.vtt
258 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/23. Convert to Z-Score-tBlCLuL2tFc.zh-CN.vtt
258 Bytes
Part 11-Module 01-Lesson 09_Clustering/08. Handoff to Katie-knrPsGtpyQY.ar.vtt
258 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.es-ES.vtt
258 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-mFm0FfWHlXw.en.vtt
257 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.zh-CN.vtt
257 Bytes
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.es-ES.vtt
257 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/04. Total Number of Samples-s0J73PTr9Rw.en.vtt
256 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic-A8xSEFaFuBc.en.vtt
256 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-ijy0n1EjY0M.ja.vtt
256 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-PaE5caOJ5kg.ar.vtt
256 Bytes
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.zh-CN.vtt
256 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.ja.vtt
256 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.pt-BR.vtt
256 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-k63Why0c1KU.en.vtt
256 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-obhHCeHpysw.zh-CN.vtt
256 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.en.vtt
256 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.en.vtt
256 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-obhHCeHpysw.zh-CN.vtt
256 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-U74HWk-E_jg.zh-CN.vtt
255 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.ja.vtt
255 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.pt-BR.vtt
255 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-k63Why0c1KU.zh-CN.vtt
255 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-DzyOcsBIncA.zh-CN.vtt
255 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200--scGDVG9KJ8.zh-CN.vtt
254 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value-5pnYBObhGJk.pt-BR.vtt
254 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-W96zaGEma7o.ja.vtt
254 Bytes
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.en.vtt
254 Bytes
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-NixhPePGk-s.pt-BR.vtt
254 Bytes
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.ar.vtt
254 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.ja.vtt
254 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.pt-BR.vtt
254 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/03. Absolute or Relative--fGYnCkj20E.pt-BR.vtt
253 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/37. Probability of Mean-dB5wr3taV7Y.pt-BR.vtt
253 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/30. Rent - Increase n-Z3Fl0WPJFoA.en.vtt
253 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2-ZEkbLbmfHvg.pt-BR.vtt
253 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-t4qaavAslSw.zh-CN.vtt
253 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.pt-BR.vtt
253 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test--Ecdsb39FnM.en.vtt
252 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/19. Finches - Decision-9cM-bc6aGTo.en.vtt
252 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price-mlNMENDGqtk.zh-CN.vtt
252 Bytes
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-Or9KvEd1flY.en.vtt
252 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-TWGqylKdGWs.en.vtt
252 Bytes
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-NixhPePGk-s.en.vtt
252 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.hr.vtt
252 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.th.vtt
252 Bytes
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.es-ES.vtt
252 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.ar.vtt
252 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-TWGqylKdGWs.en.vtt
252 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.en.vtt
251 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.en.vtt
251 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/12. Two-Tailed Probability-KwbK0InYgvE.pt-BR.vtt
251 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/16. Finches - n and DF-DvpOpY9ScQ0.pt-BR.vtt
251 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-UnkrtPPx9-c.ja.vtt
251 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price-MZyle39D5Ks.ja.vtt
251 Bytes
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-jTKkq6DdJMw.ar.vtt
251 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-r8stm2et_hI.zh-CN.vtt
251 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.es-ES.vtt
251 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-r8stm2et_hI.zh-CN.vtt
251 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/05. Mean of Each Sample-n7II63ei3LU.zh-CN.vtt
250 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/30. Sampling Distribution Shape-UMEckGyua6o.en.vtt
250 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-W96zaGEma7o.pt-BR.vtt
250 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-s_-I8mbrfw0.en.vtt
250 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-8TeKzSUGAJQ.ar.vtt
250 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.ar.vtt
250 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.zh-CN.vtt
250 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.pt-BR.vtt
249 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-2StCBxTOoK0.zh-CN.vtt
249 Bytes
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.pt-BR.vtt
249 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.pt-BR.vtt
249 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.pt-BR.vtt
249 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.pt-BR.vtt
249 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200-Ss00WF8qXHk.en.vtt
248 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/08. Probability Mean or = 3-twcNden__9M.pt-BR.vtt
248 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.zh-CN.vtt
248 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-nNna_SLlIT8.pt-BR.vtt
248 Bytes
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-yB866_TLZB8.pt-BR.vtt
248 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-T2dveKB64Ho.ar.vtt
248 Bytes
Part 13-Module 01-Lesson 04_Design Principles/42. Size of the Effect in the Graphic-D27UwulJc2c.zh-CN.vtt
248 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/18. Averaging Locations-bQQSqytU_r0.zh-CN.vtt
248 Bytes
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.zh-CN.vtt
248 Bytes
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.it.vtt
248 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.ja.vtt
248 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.en.vtt
248 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-T2dveKB64Ho.ar.vtt
248 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/19. Average Deviation-4e4jMjA9pVk.pt-BR.vtt
247 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/04. Probability Greater-SJ9JldQSF5w.pt-BR.vtt
247 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/26. t-Statistic-KvaW3rL7u4k.zh-CN.vtt
247 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-oNTklG8dh-0.en.vtt
247 Bytes
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-IC-fo_A0PxQ.pt-BR.vtt
247 Bytes
Part 13-Module 01-Lesson 04_Design Principles/42. Size of the Effect in the Graphic-nahhIlT8uSs.pt-BR.vtt
247 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/18. Averaging Locations-bQQSqytU_r0.pt-BR.vtt
247 Bytes
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.ja.vtt
247 Bytes
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.en.vtt
247 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.ja.vtt
247 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-MFN6EMAzz_k.es.vtt
246 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/25. Squared Deviations-oA37LlWNYCw.zh-CN.vtt
246 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/38. Bessel's Correction-fghrG_GXWhw.en.vtt
246 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-0r9S6UNDRu8.en.vtt
246 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/19. Finches - Decision-9cM-bc6aGTo.zh-CN.vtt
246 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.ja.vtt
246 Bytes
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-yB866_TLZB8.en.vtt
246 Bytes
Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-Z2bA98cBS4Q.en.vtt
246 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.en.vtt
246 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.pt-BR.vtt
246 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-MFN6EMAzz_k.pt-BR.vtt
245 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic-HruTS4wHpVQ.en.vtt
245 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/30. Rent - Increase n-Z3Fl0WPJFoA.zh-CN.vtt
245 Bytes
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.zh-CN.vtt
245 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.en.vtt
245 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/35. Keyboards - t-Statistic-aE-ZZw8QVWo.zh-CN.vtt
244 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-YNfxSsQT78Y.ar.vtt
244 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-s_-I8mbrfw0.zh-CN.vtt
244 Bytes
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-NixhPePGk-s.zh-CN.vtt
244 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.en.vtt
244 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.zh-CN.vtt
244 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.th.vtt
244 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-lNjXzIxTRmI.pt-BR.vtt
243 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/09. One-Tailed t-Test-ycVGpvTfoso.pt-BR.vtt
243 Bytes
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-Or9KvEd1flY.ja.vtt
243 Bytes
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.zh-CN.vtt
243 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.ja.vtt
243 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.es-ES.vtt
243 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/03. Absolute or Relative--fGYnCkj20E.en.vtt
242 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.es-ES.vtt
242 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/20. SD of Standardized Distribution-0JZyJ5_T858.zh-CN.vtt
241 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio-R2a1wC3k0JM.zh-CN.vtt
241 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/21. t-Critical-uZk43roQbt0.en.vtt
241 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/22. SEM-Sv8q6DpXOA0.en.vtt
241 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma-VMkt5knD4VU.pt-BR.vtt
241 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-wzNCL-MJ2bc.ar.vtt
241 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-TWGqylKdGWs.zh-CN.vtt
241 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.zh-CN.vtt
241 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.en.vtt
241 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.ja.vtt
241 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-TWGqylKdGWs.zh-CN.vtt
241 Bytes
How you can help Team-FTU.txt
241 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-h9IP6OuMQrk.zh-CN.vtt
240 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/04. Total Number of Samples-s0J73PTr9Rw.zh-CN.vtt
240 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.hi.vtt
240 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/13. Two-Tailed Critical Values 0.01-Kb_OuJuCFH0.en.vtt
240 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/14. Two-Tailed Critical Values 0.001-sqOOrXKazFw.en.vtt
240 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2-ZEkbLbmfHvg.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference-eTNZnE_O_RM.en.vtt
240 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-k63Why0c1KU.pt-BR.vtt
240 Bytes
Part 13-Module 01-Lesson 02_D3 Building Blocks/09. -5GuI-r2Dj1Y.en-US.vtt
240 Bytes
Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-Z2bA98cBS4Q.pt-BR.vtt
240 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.en.vtt
240 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.it.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.th.vtt
240 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.th.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.pt-BR.vtt
240 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/21. Visualize P-Value-GHw4SRGYd5Y.en.vtt
239 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error-cLyzI4feDEw.zh-CN.vtt
239 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.pt-BR.vtt
239 Bytes
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-IC-fo_A0PxQ.en.vtt
239 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.it.vtt
239 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.es-ES.vtt
239 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210-pX6RbiR-4PM.en.vtt
238 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/21. Shape of Distribution When n Increases-YT3sdKcl3Vg.pt-BR.vtt
238 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/36. Keyboards - t-Critical Values-DS_4EiegbtQ.pt-BR.vtt
238 Bytes
Part 11-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.ar.vtt
238 Bytes
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-T-dTpFd7EO0.en.vtt
238 Bytes
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.hr.vtt
238 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.en.vtt
238 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.es-ES.vtt
238 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.ar.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio-R2a1wC3k0JM.en.vtt
237 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/16. Finches - n and DF-DvpOpY9ScQ0.en.vtt
237 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-ijy0n1EjY0M.pt-BR.vtt
237 Bytes
Part 13-Module 01-Lesson 02_D3 Building Blocks/09. -5GuI-r2Dj1Y.en.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.ja.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/19. Average Deviation-4e4jMjA9pVk.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-oNTklG8dh-0.zh-CN.vtt
236 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.ja.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.es-ES.vtt
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Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-eSZ1kr_yZFg.zh-CN.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less-1PkuYCWwc_g.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom-GOwsOqdMY8w.pt-BR.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma-VMkt5knD4VU.en.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.es-ES.vtt
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Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.it.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.es-ES.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.ar.vtt
234 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median-zQzgB8KovNU.en.vtt
233 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/03. Absolute or Relative--fGYnCkj20E.zh-CN.vtt
233 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/17. Evidence to Reject the Null-BHRLT1tJXHU.en.vtt
233 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/30. r^2-L9Wwg8AQk4M.pt-BR.vtt
233 Bytes
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.zh-CN.vtt
233 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-J6RyUyWxrM4.pt-BR.vtt
233 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.es-ES.vtt
233 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/38. Bessel's Correction-fghrG_GXWhw.pt-BR.vtt
232 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-FBRK-XwPC54.ja.vtt
232 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-j1vFBL3khh0.en.vtt
232 Bytes
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-T-dTpFd7EO0.pt-BR.vtt
232 Bytes
Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-bAZJT4xHiXM.zh-CN.vtt
232 Bytes
Part 13-Module 01-Lesson 04_Design Principles/42. Size of the Effect in the Graphic-nahhIlT8uSs.en.vtt
232 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.zh-CN.vtt
232 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/04. Probability Greater-SJ9JldQSF5w.en.vtt
231 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-sMLnEgg2lqE.ar.vtt
231 Bytes
Part 13-Module 01-Lesson 08_Animation and Interaction/18. Averaging Locations-bQQSqytU_r0.en.vtt
231 Bytes
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.en.vtt
231 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.it.vtt
231 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.es-ES.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/14. Andy - SDs Below-4VKOJowrOoU.en.vtt
230 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means-TpsMv7isR6U.zh-CN.vtt
230 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price-MZyle39D5Ks.pt-BR.vtt
230 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron-MetxO9LDp-I.pt-BR.vtt
230 Bytes
Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.zh-CN.vtt
229 Bytes
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.zh-CN.vtt
229 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-MFN6EMAzz_k.en.vtt
229 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/27. Average Squared Deviation-xW3JXTmUlEE.pt-BR.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200-Ss00WF8qXHk.zh-CN.vtt
229 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/35. Keyboards - t-Statistic-JwrCtWoPBjo.en.vtt
229 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/27. Statistically Significant-VXgMxs0tiBw.zh-CN.vtt
229 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/14. Acne Medication - Decision-GCk9hNs1uxY.zh-CN.vtt
229 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-J6RyUyWxrM4.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-lNjXzIxTRmI.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/22. Absolute Deviations-pFyPTDVN41Q.en.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/11. Generalize Point Estimate-JveZxEnq9bI.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/35. Keyboards - t-Statistic-JwrCtWoPBjo.pt-BR.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/14. Acne Medication - Decision-GCk9hNs1uxY.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error-ksf2wklgpZ8.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-oNTklG8dh-0.pt-BR.vtt
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Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.th.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.es-ES.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/21. Visualize P-Value-GHw4SRGYd5Y.pt-BR.vtt
226 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.pt-BR.vtt
226 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-GtiLFC7EgFE.ja.vtt
226 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-Thj7e55iSlA.ar.vtt
226 Bytes
Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-QfIgUDXPhi8.zh-CN.vtt
226 Bytes
Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.pt-BR.vtt
226 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.zh-CN.vtt
226 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/14. Dependent Variable-nEr-E8WZ-bo.en.vtt
225 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-T4GbEVybNlY.ar.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-WmnGwUCW-Yc.pt-BR.vtt
225 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.ja.vtt
225 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.zh-CN.vtt
225 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-3R0LfaKa-fw.pt-BR.vtt
224 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-SHAt1I_VNys.es.vtt
224 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-lNjXzIxTRmI.es.vtt
224 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median-zQzgB8KovNU.zh-CN.vtt
224 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/33. Probability of Obtaining Mean-wQ3iwH9b10w.en.vtt
224 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom-58Mh3hOraqk.en.vtt
224 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value-5pnYBObhGJk.en.vtt
224 Bytes
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-Or9KvEd1flY.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.en.vtt
224 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-HvOjcTFlVTI.pt-BR.vtt
223 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/08. Probability Mean or = 3-twcNden__9M.en.vtt
223 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean-p3e965clFyU.en.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/25. Rent - Decision-s7JS53yUHN0.pt-BR.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/21. t-Critical-uZk43roQbt0.pt-BR.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.pt-BR.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.pt-BR.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210-pX6RbiR-4PM.zh-CN.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/11. Relationship Between SDs-8mHK1E3mR4E.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/16. Finches - n and DF-DvpOpY9ScQ0.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/37. Keyboards - Decision-U_FXY3uR4r0.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-FBRK-XwPC54.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-PDqyWzZCVBY.zh-CN.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron-MetxO9LDp-I.zh-CN.vtt
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Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-QfIgUDXPhi8.pt-BR.vtt
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Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-Z2bA98cBS4Q.zh-CN.vtt
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Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.ar.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-DVr1RodIqBw.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-SHAt1I_VNys.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262-ulXPRo2lgC8.en.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/33. Probability of Obtaining Mean-wQ3iwH9b10w.zh-CN.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/22. SEM-Sv8q6DpXOA0.pt-BR.vtt
221 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.es-ES.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-dSgIDN1gz5k.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/38. Bessel's Correction-fghrG_GXWhw.zh-CN.vtt
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Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-0r9S6UNDRu8.zh-Hans.vtt
220 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/17. Evidence to Reject the Null-BHRLT1tJXHU.zh-CN.vtt
220 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/37. Increase Engagement-o0gtllaVkuE.pt-BR.vtt
220 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic-aBdP9_JBhAs.pt-BR.vtt
220 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma-VMkt5knD4VU.zh-CN.vtt
220 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-W96zaGEma7o.en.vtt
220 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price--9CHGW25yMg.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-PDqyWzZCVBY.ja.vtt
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Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-T-dTpFd7EO0.zh-CN.vtt
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Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-QfIgUDXPhi8.en.vtt
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-UnkrtPPx9-c.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-ijy0n1EjY0M.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-ijy0n1EjY0M.zh-CN.vtt
219 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-FBRK-XwPC54.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-yWPbe8onCeA.en.vtt
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Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-rHBJuhoajXE.ar.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.ja.vtt
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Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.pt-BR.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.en.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.es-ES.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-lNjXzIxTRmI.zh-CN.vtt
218 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/33. Keyboards Point Estimate for Difference-1Nn61ad1UOQ.en.vtt
218 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-Nn_8kCRYn2k.ar.vtt
218 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-0bEbJ33dUis.ar.vtt
218 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.pt-BR.vtt
218 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.zh-CN.vtt
218 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-Nn_8kCRYn2k.ar.vtt
218 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-0bEbJ33dUis.ar.vtt
218 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/04. Relative Frequency Histogram-gPTaXk37UYY.en.vtt
217 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom-58Mh3hOraqk.pt-BR.vtt
217 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-YNfxSsQT78Y.pt-BR.vtt
217 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.en.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.ja.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.es-ES.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less-1PkuYCWwc_g.zh-CN.vtt
216 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.en.vtt
216 Bytes
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.hr.vtt
216 Bytes
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.ja.vtt
216 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.zh-CN.vtt
216 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.pt-BR.vtt
216 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.en.vtt
216 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-0r9S6UNDRu8.zh-CN.vtt
215 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/13. Two-Tailed Critical Values 0.01-Kb_OuJuCFH0.zh-CN.vtt
215 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/19. Finches - Decision-9cM-bc6aGTo.pt-BR.vtt
215 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/33. Keyboards Point Estimate for Difference-1Nn61ad1UOQ.pt-BR.vtt
215 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.pt-BR.vtt
215 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.pt-PT.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.zh-CN.vtt
215 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-mFm0FfWHlXw.zh-CN.vtt
214 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/37. Probability of Mean-dB5wr3taV7Y.en.vtt
214 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/12. Two-Tailed Probability-KwbK0InYgvE.en.vtt
214 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/21. Visualize P-Value-GHw4SRGYd5Y.zh-CN.vtt
214 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price-MZyle39D5Ks.en.vtt
214 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron-MetxO9LDp-I.en.vtt
214 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.en.vtt
214 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.zh-CN.vtt
214 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.en.vtt
214 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/04. Relative Frequency Histogram-gPTaXk37UYY.pt-BR.vtt
213 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.zh-CN.vtt
213 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-8fM13xqU2a8.en.vtt
213 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.hr.vtt
213 Bytes
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.it.vtt
213 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-8fM13xqU2a8.en.vtt
213 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/09. Between 118 and 226-b2t55uKFMrA.pt-BR.vtt
212 Bytes
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-Or9KvEd1flY.zh-CN.vtt
212 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price--9CHGW25yMg.zh-CN.vtt
212 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-PaE5caOJ5kg.en.vtt
212 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.it.vtt
212 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.ja.vtt
212 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.zh-CN.vtt
212 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.zh-CN.vtt
212 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.pt-BR.vtt
212 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-Qc81PeO-YYU.es.vtt
211 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-T4GbEVybNlY.ja.vtt
211 Bytes
Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete-4yapJV56YoM.zh-CN.vtt
211 Bytes
Part 13-Module 01-Lesson 02_D3 Building Blocks/09. -5GuI-r2Dj1Y.zh-CN.vtt
211 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.ar.vtt
211 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-SHAt1I_VNys.pt-BR.vtt
210 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-MFN6EMAzz_k.zh-CN.vtt
210 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/24. t-Statistic-rWiQoVHAa0s.en.vtt
210 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic-aBdP9_JBhAs.en.vtt
210 Bytes
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-ppSLADGROp8.ar.vtt
210 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-WmnGwUCW-Yc.en.vtt
210 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.es-ES.vtt
210 Bytes
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.en.vtt
210 Bytes
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.it.vtt
210 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.zh-CN.vtt
210 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-Qc81PeO-YYU.en.vtt
209 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/30. Sampling Distribution Shape-UMEckGyua6o.zh-CN.vtt
209 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/14. Two-Tailed Critical Values 0.001-sqOOrXKazFw.pt-BR.vtt
209 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.hr.vtt
209 Bytes
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.pt-BR.vtt
209 Bytes
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Tidiness-LSdhieL7nXU.zh-CN.vtt
209 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-dSgIDN1gz5k.zh-CN.vtt
208 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/27. Average Squared Deviation-xW3JXTmUlEE.en.vtt
208 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/14. Andy - SDs Below-4VKOJowrOoU.zh-CN.vtt
208 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom-GOwsOqdMY8w.en.vtt
208 Bytes
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-IC-fo_A0PxQ.zh-CN.vtt
208 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-sPqs7DoBkXQ.en.vtt
208 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.ar.vtt
208 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/04. Probability Greater-SJ9JldQSF5w.zh-CN.vtt
207 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/37. Probability of Mean-dB5wr3taV7Y.zh-CN.vtt
207 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject-Nl5RzE-RQHA.en.vtt
207 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-UnkrtPPx9-c.en.vtt
207 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.zh-CN.vtt
207 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.zh-CN.vtt
207 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-PDqyWzZCVBY.pt-BR.vtt
207 Bytes
Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete-4yapJV56YoM.en.vtt
207 Bytes
Part 11-Module 01-Lesson 09_Clustering/08. Handoff to Katie-knrPsGtpyQY.en.vtt
207 Bytes
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.ar.vtt
207 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.zh-CN.vtt
207 Bytes
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Tidiness-LSdhieL7nXU.en.vtt
207 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/09. Between 118 and 226-b2t55uKFMrA.en.vtt
206 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/08. Probability Mean or = 3-twcNden__9M.zh-CN.vtt
206 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject-Nl5RzE-RQHA.zh-CN.vtt
206 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/14. Dependent Variable-nEr-E8WZ-bo.pt-BR.vtt
206 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/14. Dependent Variable-nEr-E8WZ-bo.zh-CN.vtt
206 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/24. Calculate Pooled Variance-jNfrnjMn7dU.pt-BR.vtt
206 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-W96zaGEma7o.zh-CN.vtt
206 Bytes
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-jTKkq6DdJMw.pt-BR.vtt
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Part 11-Module 01-Lesson 09_Clustering/08. Handoff to Katie-knrPsGtpyQY.zh-CN.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/36. Keyboards - t-Critical Values-DS_4EiegbtQ.en.vtt
205 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/24. t-Statistic-rWiQoVHAa0s.pt-BR.vtt
205 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/24. t-Statistic-rWiQoVHAa0s.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-YNfxSsQT78Y.ja.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-WmnGwUCW-Yc.ja.vtt
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Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete-4yapJV56YoM.pt-BR.vtt
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Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.en.vtt
205 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.it.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.th.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions--xSSuPcrrA8.pt-BR.vtt
204 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic-HruTS4wHpVQ.zh-CN.vtt
204 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-yWPbe8onCeA.zh-CN.vtt
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Part 11-Module 01-Lesson 09_Clustering/08. Handoff to Katie-knrPsGtpyQY.pt-BR.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-OdsfV143AMc.ar.vtt
204 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-8fM13xqU2a8.zh-CN.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.ar.vtt
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Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.hr.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.th.vtt
204 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-8fM13xqU2a8.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-dSgIDN1gz5k.es.vtt
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Part 03-Module 01-Lesson 13_L5 Standardizing/03. Absolute or Relative-kQtW3r36-Lc.pt-BR.vtt
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/09. One-Tailed t-Test-ycVGpvTfoso.en.vtt
203 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/25. Rent - Decision-s7JS53yUHN0.en.vtt
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/28. Meaningful Results-7LoVF_V0qZ4.en.vtt
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Part 11-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.en.vtt
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Part 11-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-th34aboBOO0.ar.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-8fM13xqU2a8.pt-BR.vtt
203 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-8fM13xqU2a8.pt-BR.vtt
203 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-Qc81PeO-YYU.pt-BR.vtt
202 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error-ksf2wklgpZ8.zh-CN.vtt
202 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.ar.vtt
202 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.pt-BR.vtt
202 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.ja.vtt
202 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262-ulXPRo2lgC8.pt-BR.vtt
201 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/09. Between 118 and 226-b2t55uKFMrA.zh-CN.vtt
201 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/21. Shape of Distribution When n Increases-YT3sdKcl3Vg.zh-CN.vtt
201 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject-Nl5RzE-RQHA.pt-BR.vtt
201 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/21. t-Critical-uZk43roQbt0.zh-CN.vtt
201 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/28. Meaningful Results-7LoVF_V0qZ4.pt-BR.vtt
201 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price-MZyle39D5Ks.zh-CN.vtt
201 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-PaE5caOJ5kg.pt-BR.vtt
201 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-YNfxSsQT78Y.en.vtt
201 Bytes
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-jTKkq6DdJMw.en.vtt
201 Bytes
Part 13-Module 01-Lesson 04_Design Principles/42. Size of the Effect in the Graphic-nahhIlT8uSs.zh-CN.vtt
201 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.ja.vtt
201 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.pt-BR.vtt
201 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/14. Two-Tailed Critical Values 0.001-sqOOrXKazFw.zh-CN.vtt
200 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/35. To Finish This Lesson...-vwRvT9b7IEE.en.vtt
200 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-YNfxSsQT78Y.zh-CN.vtt
200 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.ja.vtt
200 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-HvOjcTFlVTI.en.vtt
199 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/21. Shape of Distribution When n Increases-YT3sdKcl3Vg.en.vtt
199 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/14. Increase t--ypzhIBAuvg.zh-CN.vtt
199 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/16. Finches - n and DF-z60KPEhRSYs.en.vtt
199 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/37. Keyboards - Decision-U_FXY3uR4r0.zh-CN.vtt
199 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic-kJxLPlQC-lQ.pt-BR.vtt
199 Bytes
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/12. Congratulations-pXfWdBuWw74.zh-CN.vtt
199 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-GtiLFC7EgFE.pt-BR.vtt
199 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.ja.vtt
199 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-PDqyWzZCVBY.en.vtt
199 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.ja.vtt
199 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/22. Absolute Deviations-pFyPTDVN41Q.pt-BR.vtt
198 Bytes
Part 13-Module 01-Lesson 04_Design Principles/43. Calculating the Lie Factor-CtIN6dfd-h4.pt-BR.vtt
198 Bytes
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.en.vtt
198 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.zh-CN.vtt
198 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.ja.vtt
198 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2-ZEkbLbmfHvg.zh-CN.vtt
197 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/28. Meaningful Results-7LoVF_V0qZ4.zh-CN.vtt
197 Bytes
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.zh-CN.vtt
197 Bytes
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.hr.vtt
197 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.ja.vtt
197 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-yWPbe8onCeA.ja.vtt
196 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-yWPbe8onCeA.pt-BR.vtt
196 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces-jkjr_prWyt8.ar.vtt
196 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.en.vtt
196 Bytes
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.zh-CN.vtt
196 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces-jkjr_prWyt8.ar.vtt
196 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/23. Average Absolute Deviation--S35dQNbjhc.pt-BR.vtt
195 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/22. SEM-Sv8q6DpXOA0.zh-CN.vtt
195 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/05. SD for Meal Price-_BPrFUlWcXo.pt-BR.vtt
195 Bytes
Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-rHBJuhoajXE.pt-BR.vtt
195 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/05. Does Range Change-SLl0i0SKwHU.zh-CN.vtt
194 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/14. Increase t--ypzhIBAuvg.en.vtt
194 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic-aBdP9_JBhAs.zh-CN.vtt
194 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-GtiLFC7EgFE.en.vtt
194 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-j1vFBL3khh0.zh-CN.vtt
194 Bytes
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.ja.vtt
194 Bytes
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.ja.vtt
194 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-RF_DpOg--PY.en.vtt
193 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-SHAt1I_VNys.zh-CN.vtt
193 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/35. To Finish This Lesson...-vwRvT9b7IEE.pt-BR.vtt
193 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic-kJxLPlQC-lQ.en.vtt
193 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-T4GbEVybNlY.en.vtt
193 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-PaE5caOJ5kg.ja.vtt
193 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/05. Critical Values 0.001-h72200GCyaI.en.vtt
192 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom-58Mh3hOraqk.zh-CN.vtt
192 Bytes
Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-rHBJuhoajXE.zh-CN.vtt
192 Bytes
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.es-ES.vtt
192 Bytes
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.zh-CN.vtt
192 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-RF_DpOg--PY.zh-CN.vtt
191 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/19. Average Deviation-4e4jMjA9pVk.zh-CN.vtt
191 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/25. Rent - Decision-s7JS53yUHN0.zh-CN.vtt
191 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-PaE5caOJ5kg.zh-CN.vtt
191 Bytes
Part 11-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.zh-CN.vtt
191 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.ar.vtt
191 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/16. Finches - n and DF-z60KPEhRSYs.pt-BR.vtt
190 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/37. Keyboards - Decision-U_FXY3uR4r0.pt-BR.vtt
190 Bytes
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8TqVHRan4Fo.ja.vtt
190 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-WmnGwUCW-Yc.zh-CN.vtt
190 Bytes
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.en.vtt
190 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.ja.vtt
190 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.ar.vtt
190 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-RaXs536nNkg.en.vtt
189 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/05. Does Range Change-SLl0i0SKwHU.pt-BR.vtt
189 Bytes
Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262-ulXPRo2lgC8.zh-CN.vtt
189 Bytes
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8TqVHRan4Fo.zh-CN.vtt
189 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-8TeKzSUGAJQ.pt-BR.vtt
189 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.zh-Hans.vtt
189 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference-eTNZnE_O_RM.zh-CN.vtt
188 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-UnkrtPPx9-c.zh-CN.vtt
188 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-T4GbEVybNlY.pt-BR.vtt
188 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-i6aCKjMeZPk.ar.vtt
188 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.pt-BR.vtt
188 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.pt-BR.vtt
188 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-HvOjcTFlVTI.es.vtt
187 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/05. Does Range Change-SLl0i0SKwHU.en.vtt
187 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic-A8xSEFaFuBc.zh-CN.vtt
187 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/35. Keyboards - t-Statistic-JwrCtWoPBjo.zh-CN.vtt
187 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-FlbDcNPGgUE.ar.vtt
187 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.ar.vtt
187 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-i6aCKjMeZPk.ja.vtt
187 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-0bEbJ33dUis.zh-CN.vtt
187 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.it.vtt
187 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.ja.vtt
187 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-0bEbJ33dUis.zh-CN.vtt
187 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-HvOjcTFlVTI.zh-CN.vtt
186 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/03. Absolute or Relative-kQtW3r36-Lc.en.vtt
186 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-sPqs7DoBkXQ.pt-BR.vtt
186 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.en.vtt
186 Bytes
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.pt-BR.vtt
186 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.zh-CN.vtt
186 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.en.vtt
186 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/22. Absolute Deviations-pFyPTDVN41Q.zh-CN.vtt
185 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value-5pnYBObhGJk.zh-CN.vtt
185 Bytes
Part 11-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.pt-BR.vtt
185 Bytes
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8TqVHRan4Fo.en.vtt
185 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-GtiLFC7EgFE.zh-CN.vtt
185 Bytes
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.es-ES.vtt
185 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-oNRtSJvtkJc.pt-BR.vtt
184 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/05. Critical Values 0.001-AdLGLYYYVao.pt-BR.vtt
184 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-3tzTP3e0Cjw.ar.vtt
184 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-i6aCKjMeZPk.en.vtt
184 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.ar.vtt
184 Bytes
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.pt-BR.vtt
184 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.ja.vtt
184 Bytes
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/12. Congratulations-pXfWdBuWw74.en.vtt
183 Bytes
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.zh-CN.vtt
183 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.pt-BR.vtt
183 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/35. To Finish This Lesson...-vwRvT9b7IEE.zh-CN.vtt
182 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-FBRK-XwPC54.zh-CN.vtt
182 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-Nn_8kCRYn2k.en.vtt
182 Bytes
Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-rHBJuhoajXE.en.vtt
182 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.zh-CN.vtt
182 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-Nn_8kCRYn2k.en.vtt
182 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-RaXs536nNkg.zh-CN.vtt
181 Bytes
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-ppSLADGROp8.ja.vtt
181 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-i6aCKjMeZPk.pt-BR.vtt
181 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-wzNCL-MJ2bc.en.vtt
181 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-oxsmq36m5kQ.pt-BR.vtt
180 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-Qc81PeO-YYU.zh-CN.vtt
180 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/09. One-Tailed t-Test-ycVGpvTfoso.zh-CN.vtt
180 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/33. Keyboards Point Estimate for Difference-1Nn61ad1UOQ.zh-CN.vtt
180 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-OdsfV143AMc.pt-BR.vtt
180 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.zh-CN.vtt
180 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.zh-CN.vtt
180 Bytes
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.en.vtt
180 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.ja.vtt
180 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.zh-CN.vtt
180 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-RaXs536nNkg.es.vtt
178 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-T2dveKB64Ho.en.vtt
178 Bytes
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.it.vtt
178 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.th.vtt
178 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-T2dveKB64Ho.en.vtt
178 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/29. Klout Sampling Distribution (SD)-ylUUpaUfFEY.pt-BR.vtt
177 Bytes
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8TqVHRan4Fo.pt-BR.vtt
177 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-wzNCL-MJ2bc.pt-BR.vtt
177 Bytes
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-jTKkq6DdJMw.zh-CN.vtt
177 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-Nn_8kCRYn2k.pt-BR.vtt
177 Bytes
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.zh-CN.vtt
177 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.th.vtt
177 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-Nn_8kCRYn2k.pt-BR.vtt
177 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-T4GbEVybNlY.zh-CN.vtt
176 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-dk3FxGVdP7Q.ar.vtt
176 Bytes
Part 13-Module 01-Lesson 04_Design Principles/43. Calculating the Lie Factor-CtIN6dfd-h4.ar.vtt
176 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.ar.vtt
176 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.ja.vtt
176 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-DVr1RodIqBw.es.vtt
175 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-fD6jd1ac3sk.pt-BR.vtt
175 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/34. Does Low Probability = Causation-l86zVvAfjNA.pt-BR.vtt
175 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/36. Keyboards - t-Critical Values-DS_4EiegbtQ.zh-CN.vtt
175 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.ar.vtt
175 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.ja.vtt
175 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces-jkjr_prWyt8.en.vtt
174 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.es-ES.vtt
174 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.it.vtt
174 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.es-ES.vtt
174 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces-jkjr_prWyt8.en.vtt
174 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-oxsmq36m5kQ.es.vtt
173 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/03. Absolute or Relative-kQtW3r36-Lc.zh-CN.vtt
173 Bytes
Part 03-Module 01-Lesson 13_L5 Standardizing/04. Relative Frequency Histogram-gPTaXk37UYY.zh-CN.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.it.vtt
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172 Bytes
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Part 11-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron--dT9dztM-Lc.ar.vtt
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171 Bytes
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.it.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.it.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces-jkjr_prWyt8.pt-BR.vtt
170 Bytes
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Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces-jkjr_prWyt8.pt-BR.vtt
170 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-8TeKzSUGAJQ.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.pt-BR.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.en.vtt
169 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.pt-BR.vtt
169 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/27. Statistically Significant-y7Kk4Aywtrg.pt-BR.vtt
168 Bytes
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality--dcNhrSPmoY.ar.vtt
168 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.en.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-8TeKzSUGAJQ.en.vtt
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Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.zh-CN.vtt
167 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-T2dveKB64Ho.pt-BR.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.en.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-T2dveKB64Ho.pt-BR.vtt
167 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/05. Critical Values 0.001-h72200GCyaI.zh-CN.vtt
166 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom-GOwsOqdMY8w.zh-CN.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-wzNCL-MJ2bc.zh-CN.vtt
166 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-OdsfV143AMc.zh-CN.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-sPqs7DoBkXQ.zh-CN.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.es-ES.vtt
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Part 11-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.ja.vtt
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Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-ppSLADGROp8.pt-BR.vtt
165 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-J6RyUyWxrM4.zh-CN.vtt
165 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.en.vtt
165 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.es-ES.vtt
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164 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-OdsfV143AMc.en.vtt
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Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.zh-CN.vtt
164 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.th.vtt
164 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.it.vtt
164 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.pt-BR.vtt
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Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-ppSLADGROp8.en.vtt
163 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.hr.vtt
163 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-0bEbJ33dUis.en.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-0bEbJ33dUis.en.vtt
161 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/16. Finches - n and DF-z60KPEhRSYs.zh-CN.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.pt-BR.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-Nn_8kCRYn2k.zh-CN.vtt
160 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.es-ES.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.th.vtt
160 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-Nn_8kCRYn2k.zh-CN.vtt
160 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/20. Alternative Hypothesis-ferT-sqV3A0.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-3tzTP3e0Cjw.pt-BR.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-sMLnEgg2lqE.pt-BR.vtt
159 Bytes
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.ja.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.zh-CN.vtt
158 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.zh-CN.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-ypEVJhggHQc.es.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.zh-CN.vtt
157 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-F-xSYJ3y_pA.ar.vtt
157 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces-jkjr_prWyt8.zh-CN.vtt
157 Bytes
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.hr.vtt
157 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.ja.vtt
157 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.es-ES.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.pt-BR.vtt
157 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces-jkjr_prWyt8.zh-CN.vtt
157 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.ko.vtt
156 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.ja.vtt
156 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-jO81hfubpXY.pt-BR.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.en.vtt
155 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.zh-CN.vtt
155 Bytes
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.hr.vtt
155 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.ja.vtt
155 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.es-ES.vtt
155 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.en.vtt
155 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-jO81hfubpXY.pt-BR.vtt
155 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.ja.vtt
154 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-3tzTP3e0Cjw.en.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.zh-CN.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.ar.vtt
153 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-RaXs536nNkg.pt-BR.vtt
152 Bytes
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic-kJxLPlQC-lQ.zh-CN.vtt
152 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-3tzTP3e0Cjw.ja.vtt
152 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-3tzTP3e0Cjw.zh-CN.vtt
152 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.zh-CN.vtt
152 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.en.vtt
152 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.th.vtt
152 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.ar.vtt
152 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-oNRtSJvtkJc.en.vtt
151 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.it.vtt
151 Bytes
Part 11-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-jO81hfubpXY.zh-CN.vtt
150 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.zh-CN.vtt
150 Bytes
Part 17-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-jO81hfubpXY.zh-CN.vtt
150 Bytes
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/12. Congratulations-pXfWdBuWw74.pt-BR.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-v2UbL0SOm9A.ja.vtt
149 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.pt-BR.vtt
149 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.hr.vtt
149 Bytes
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.ja.vtt
149 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.zh-CN.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.zh-CN.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.en.vtt
148 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-DVr1RodIqBw.en.vtt
147 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/29. Cohen's d--x9e6NP_ac0.pt-BR.vtt
147 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.en.vtt
147 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.en.vtt
146 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.pt-BR.vtt
146 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions--xSSuPcrrA8.es.vtt
144 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-fD6jd1ac3sk.zh-CN.vtt
144 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-oNRtSJvtkJc.zh-CN.vtt
144 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/23. Average Absolute Deviation-MNJlXsuCuyo.en.vtt
144 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.hr.vtt
144 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.ar.vtt
144 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-FlbDcNPGgUE.en.vtt
143 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-Thj7e55iSlA.pt-BR.vtt
143 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.es-ES.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-jO81hfubpXY.en.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-T2dveKB64Ho.zh-CN.vtt
142 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.es-ES.vtt
142 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.ja.vtt
142 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.en.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-jO81hfubpXY.en.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-T2dveKB64Ho.zh-CN.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/10. Less than 240-ZeIYb60Qerk.en.vtt
141 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/26. Rent - Cohen's d-k7eajev401c.en.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron--dT9dztM-Lc.en.vtt
141 Bytes
Part 11-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-th34aboBOO0.pt-BR.vtt
141 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.es-ES.vtt
141 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.ar.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.ja.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.ja.vtt
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.es-ES.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/23. Average Absolute Deviation-MNJlXsuCuyo.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/11. Relationship Between SDs-nG9l9ba7TrE.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/34. Does Low Probability = Causation-l86zVvAfjNA.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/05. SD for Meal Price-_BPrFUlWcXo.en.vtt
140 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-Thj7e55iSlA.en.vtt
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Part 11-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-vmIK4jpUtNo.ar.vtt
140 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.en.vtt
140 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.es-ES.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-oxsmq36m5kQ.en.vtt
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Part 11-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-th34aboBOO0.en.vtt
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Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.ja.vtt
139 Bytes
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality--dcNhrSPmoY.en.vtt
138 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.en.vtt
138 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.it.vtt
138 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.ja.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.es-ES.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-dyShKWpTo-c.en.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.ja.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.th.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-dyShKWpTo-c.en.vtt
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Part 03-Module 01-Lesson 11_L4 Variability/23. Average Absolute Deviation--S35dQNbjhc.en.vtt
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/10. Less than 240-ZeIYb60Qerk.pt-BR.vtt
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/28. Klout Sampling Distribution (Mean)-_yD3iz4bFhc.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-v2UbL0SOm9A.ar.vtt
136 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.zh-CN.vtt
136 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.th.vtt
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/20. Alternative Hypothesis-ferT-sqV3A0.en.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-dk3FxGVdP7Q.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.ja.vtt
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Part 11-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-dyShKWpTo-c.pt-BR.vtt
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Part 17-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-dyShKWpTo-c.pt-BR.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-u4rfZfA2ANk.en.vtt
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/24. Calculate Pooled Variance-jNfrnjMn7dU.en.vtt
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Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.ar.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.ja.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-FlbDcNPGgUE.ja.vtt
131 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-F-xSYJ3y_pA.en.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-F-xSYJ3y_pA.ja.vtt
131 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-u4rfZfA2ANk.es.vtt
130 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/29. Cohen's d--x9e6NP_ac0.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-v2UbL0SOm9A.pt-BR.vtt
130 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-sMLnEgg2lqE.en.vtt
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Part 11-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-dk3FxGVdP7Q.en.vtt
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Part 13-Module 01-Lesson 04_Design Principles/43. Calculating the Lie Factor-CtIN6dfd-h4.en.vtt
130 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.es-ES.vtt
130 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.th.vtt
130 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.en.vtt
130 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions--xSSuPcrrA8.en.vtt
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-fD6jd1ac3sk.en.vtt
129 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/23. Average Absolute Deviation-MNJlXsuCuyo.zh-CN.vtt
129 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.it.vtt
129 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.en.vtt
129 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.zh-CN.vtt
129 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.ar.vtt
129 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.es-ES.vtt
129 Bytes
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129 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.zh-CN.vtt
128 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/27. Statistically Significant-y7Kk4Aywtrg.en.vtt
128 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-v2UbL0SOm9A.en.vtt
128 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.en.vtt
128 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.pt-PT.vtt
127 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.zh-Hans.vtt
127 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.it.vtt
127 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.zh-CN.vtt
127 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-DVr1RodIqBw.zh-CN.vtt
126 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-ypEVJhggHQc.en.vtt
126 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-FlbDcNPGgUE.zh-CN.vtt
126 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-4oOXVejgFGk.ar.vtt
126 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.zh-CN.vtt
126 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.ja.vtt
126 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.ar.vtt
126 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-oxsmq36m5kQ.zh-CN.vtt
125 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-cJCx-Su6vx0.pt-BR.vtt
125 Bytes
Part 11-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-sMLnEgg2lqE.zh-CN.vtt
125 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-vmIK4jpUtNo.zh-CN.vtt
125 Bytes
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality--dcNhrSPmoY.zh-CN.vtt
125 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.es-ES.vtt
125 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.es-ES.vtt
125 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.pt-BR.vtt
125 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-vmIK4jpUtNo.pt-BR.vtt
124 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-ypEVJhggHQc.zh-CN.vtt
123 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/29. Klout Sampling Distribution (SD)-ylUUpaUfFEY.en.vtt
123 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-frzL4n6Y-vU.ar.vtt
123 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.zh-CN.vtt
123 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.zh-CN.vtt
123 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.ja.vtt
123 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.ja.vtt
123 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.fr.vtt
122 Bytes
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/30. r^2-L9Wwg8AQk4M.en.vtt
122 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-F-xSYJ3y_pA.pt-BR.vtt
122 Bytes
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-FZVBF1HR4U0.ar.vtt
122 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.en.vtt
122 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.ja.vtt
122 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.ar.vtt
122 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.pt-BR.vtt
122 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-FlbDcNPGgUE.pt-BR.vtt
121 Bytes
Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-kNxZwfXwvuk.ar.vtt
121 Bytes
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/37. Increase Engagement-o0gtllaVkuE.en.vtt
120 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.en.vtt
120 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.es-ES.vtt
120 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/05. Mean of Each Sample-SAdBKdiDE6w.en.vtt
119 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.es-AR.vtt
119 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.es-ES.vtt
119 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-frzL4n6Y-vU.ja.vtt
119 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.zh-Hans.vtt
119 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.en.vtt
119 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-p5p3OLARpmA.ar.vtt
118 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.en.vtt
118 Bytes
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.zh-CN.vtt
118 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.ar.vtt
118 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.es-ES.vtt
118 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.ja.vtt
118 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-u4rfZfA2ANk.zh-CN.vtt
117 Bytes
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.zh-CN.vtt
117 Bytes
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions--xSSuPcrrA8.zh-CN.vtt
116 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/23. Average Absolute Deviation--S35dQNbjhc.zh-CN.vtt
116 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.en-GB.vtt
116 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.ja.vtt
116 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.zh-CN.vtt
116 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.it.vtt
115 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.zh-CN.vtt
115 Bytes
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.en.vtt
113 Bytes
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-FZVBF1HR4U0.zh-CN.vtt
113 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.zh-CN.vtt
113 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.ja.vtt
113 Bytes
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.zh-CN.vtt
113 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/05. Mean of Each Sample-SAdBKdiDE6w.pt-BR.vtt
111 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-frzL4n6Y-vU.pt-BR.vtt
111 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.zh-CN.vtt
111 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-L4elyDe8pFk.ar.vtt
110 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-L4elyDe8pFk.pt-BR.vtt
110 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.ar.vtt
110 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.ja.vtt
110 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.en.vtt
110 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.zh-CN.vtt
110 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/38. Keyboards - Cohen's d-9TgKqnlta2U.pt-BR.vtt
109 Bytes
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-FZVBF1HR4U0.en.vtt
109 Bytes
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-FZVBF1HR4U0.pt-BR.vtt
109 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.es-ES.vtt
109 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.es-ES.vtt
109 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.en.vtt
109 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-frzL4n6Y-vU.en.vtt
108 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-vmIK4jpUtNo.en.vtt
108 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.ar.vtt
108 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.th.vtt
108 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.pt-BR.vtt
108 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.es-ES.vtt
108 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.pt-BR.vtt
108 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.zh-CN.vtt
108 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-L4elyDe8pFk.en.vtt
107 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-4oOXVejgFGk.ja.vtt
107 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-p5p3OLARpmA.zh-CN.vtt
107 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.es-ES.vtt
107 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-T9tjPHqbB6M.pt-BR.vtt
106 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-rnaZpqIqA2g.ja.vtt
106 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.pt-BR.vtt
106 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/31. Calculate SD-ZzEF7yc5208.en.vtt
105 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-p5p3OLARpmA.pt-BR.vtt
105 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-T9tjPHqbB6M.zh-CN.vtt
104 Bytes
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/11. Relationship Between SDs-nG9l9ba7TrE.en.vtt
104 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-L4elyDe8pFk.ja.vtt
104 Bytes
Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-p5p3OLARpmA.en.vtt
104 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.es-ES.vtt
104 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.en.vtt
104 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/31. Calculate SD-ZzEF7yc5208.zh-CN.vtt
103 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.en.vtt
103 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-T9tjPHqbB6M.en.vtt
101 Bytes
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/38. Keyboards - Cohen's d-9TgKqnlta2U.en.vtt
101 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-rnaZpqIqA2g.zh-CN.vtt
101 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-4oOXVejgFGk.en.vtt
101 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.pt-BR.vtt
101 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.zh-Hans.vtt
101 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.es-ES.vtt
101 Bytes
Part 03-Module 01-Lesson 11_L4 Variability/31. Calculate SD-ZzEF7yc5208.pt-BR.vtt
100 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.ja.vtt
100 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.pt-BR.vtt
100 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-JX3NN5zwL08.ar.vtt
99 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.ar.vtt
99 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.pt-BR.vtt
99 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.zh-CN.vtt
99 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.pt-BR.vtt
99 Bytes
Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-T9tjPHqbB6M.es.vtt
98 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.zh-Hans.vtt
98 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.ar.vtt
98 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.zh-CN.vtt
98 Bytes
Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-kNxZwfXwvuk.pt-BR.vtt
97 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.ja.vtt
97 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.en.vtt
97 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.it.vtt
96 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.ar.vtt
96 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.es-ES.vtt
95 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.es-ES.vtt
95 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.en.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.hr.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.ar.vtt
95 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.en.vtt
95 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.zh-CN.vtt
94 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.ar.vtt
94 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.it.vtt
94 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.ja.vtt
94 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.pt-BR.vtt
94 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-rnaZpqIqA2g.ar.vtt
93 Bytes
Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-kNxZwfXwvuk.en.vtt
92 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.ar.vtt
92 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.pt-BR.vtt
92 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.pt-BR.vtt
91 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.ja.vtt
91 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-JX3NN5zwL08.pt-BR.vtt
90 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.en.vtt
90 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.ar.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.zh-CN.vtt
90 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.en.vtt
90 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.it.vtt
90 Bytes
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.zh-CN.vtt
90 Bytes
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-L4elyDe8pFk.zh-CN.vtt
89 Bytes
Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-JX3NN5zwL08.ja.vtt
89 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.it.vtt
89 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.pt-PT.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.it.vtt
89 Bytes
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.it.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.ja.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.pt-BR.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.en.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.en.vtt
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Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.zh-CN.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-rnaZpqIqA2g.en.vtt
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Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-rnaZpqIqA2g.pt-BR.vtt
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Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-JX3NN5zwL08.en.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.en.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.hr.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.hr.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.zh-Hans.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.hr.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.zh-CN.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.zh-CN.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.hr.vtt
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Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.tr.vtt
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