GetFreeCourses.Me-Udemy-Complete Machine Learning and Data Science Zero to Mastery

磁力链接/BT种子名称

GetFreeCourses.Me-Udemy-Complete Machine Learning and Data Science Zero to Mastery

磁力链接/BT种子简介

种子哈希：efb3aa528657ed39712bf4d25f94593b1eb872dc
文件大小： 13.26G
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收录时间：2021-03-07
最近下载：2024-11-07

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文件列表

  • 5. Data Science Environment Setup/8. Windows Environment Setup 2.mp4 238.7 MB
  • 9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.mp4 199.4 MB
  • 9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.mp4 184.7 MB
  • 17. Career Advice + Extra Bits/9. CWD Git + Github.mp4 184.7 MB
  • 9. Scikit-learn Creating Machine Learning Models/38. Tuning Hyperparameters.mp4 184.1 MB
  • 17. Career Advice + Extra Bits/3. What If I Don_t Have Enough Experience.mp4 168.8 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Feature Engineering.mp4 166.9 MB
  • 9. Scikit-learn Creating Machine Learning Models/44. Putting It All Together.mp4 166.0 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Turning Data Into Numbers.mp4 153.3 MB
  • 5. Data Science Environment Setup/5. Mac Environment Setup.mp4 151.4 MB
  • 9. Scikit-learn Creating Machine Learning Models/14. Choosing The Right Model For Your Data.mp4 150.2 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Feature Importance.mp4 149.2 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.mp4 146.1 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/9. Finding Patterns 3.mp4 144.6 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/5. Exploring Our Data.mp4 144.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/13. Getting Your Data Ready Handling Missing Values With Scikit-learn.mp4 143.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/11. Getting Your Data Ready Convert Data To Numbers.mp4 141.6 MB
  • 17. Career Advice + Extra Bits/11. Contributing To Open Source.mp4 136.6 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/20. Finding The Most Important Features.mp4 133.7 MB
  • 5. Data Science Environment Setup/6. Mac Environment Setup 2.mp4 131.6 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/18. Customizing Your Plots 2.mp4 129.7 MB
  • 9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 3.mp4 127.7 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.mp4 125.6 MB
  • 9. Scikit-learn Creating Machine Learning Models/18. Choosing The Right Model For Your Data 3 (Classification).mp4 124.6 MB
  • 17. Career Advice + Extra Bits/10. CWD Git + Github 2.mp4 124.1 MB
  • 9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together 2.mp4 122.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters 2.mp4 122.4 MB
  • 17. Career Advice + Extra Bits/12. Contributing To Open Source 2.mp4 118.5 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/14. Tuning Hyperparameters.mp4 113.2 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Filling Missing Numerical Values.mp4 111.5 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/4. Step 1~4 Framework Setup.mp4 110.6 MB
  • 6. Pandas Data Analysis/9. Manipulating Data.mp4 110.1 MB
  • 9. Scikit-learn Creating Machine Learning Models/12. Getting Your Data Ready Handling Missing Values With Pandas.mp4 109.9 MB
  • 18. Learn Python/1. What Is A Programming Language.mp4 109.9 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/15. Tuning Hyperparameters 2.mp4 109.2 MB
  • 5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough 2.mp4 108.9 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Custom Evaluation Function.mp4 108.4 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/13. TuningImproving Our Model.mp4 107.8 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.mp4 106.2 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/3. Project Environment Setup.mp4 105.7 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/8. Finding Patterns 2.mp4 104.8 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.mp4 103.6 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/11. Choosing The Right Models.mp4 101.1 MB
  • 9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model 2 (Cross Validation).mp4 100.6 MB
  • 9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Model With Scikit-learn Functions.mp4 99.4 MB
  • 18. Learn Python/16. Variables.mp4 98.1 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Reducing Data.mp4 98.0 MB
  • 18. Learn Python/2. Python Interpreter.mp4 98.0 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/17. Customizing Your Plots.mp4 96.7 MB
  • 9. Scikit-learn Creating Machine Learning Models/35. Evaluating A Model With Cross Validation and Scoring Parameter.mp4 95.9 MB
  • 7. NumPy/13. Exercise Nut Butter Store Sales.mp4 95.8 MB
  • 6. Pandas Data Analysis/11. Manipulating Data 3.mp4 95.4 MB
  • 9. Scikit-learn Creating Machine Learning Models/37. Improving A Machine Learning Model.mp4 95.4 MB
  • 9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.mp4 92.6 MB
  • 9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 6 (Classification Report).mp4 91.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/23. Evaluating A Machine Learning Model (Score).mp4 91.4 MB
  • 9. Scikit-learn Creating Machine Learning Models/15. Choosing The Right Model For Your Data 2 (Regression).mp4 91.1 MB
  • 6. Pandas Data Analysis/10. Manipulating Data 2.mp4 90.7 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/3. Importing And Using Matplotlib.mp4 90.6 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/21. Reviewing The Project.mp4 90.3 MB
  • 7. NumPy/16. Turn Images Into NumPy Arrays.mp4 90.1 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/15. RandomizedSearchCV.mp4 90.0 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/4. Step 1~4 Framework Setup.mp4 89.8 MB
  • 7. NumPy/12. Dot Product vs Element Wise.mp4 88.0 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/12. Splitting Data.mp4 86.7 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.mp4 86.1 MB
  • 18. Learn Python/5. Python 2 vs Python 3.mp4 86.1 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.mp4 86.0 MB
  • 7. NumPy/8. Manipulating Arrays.mp4 84.6 MB
  • 13. Data Engineering/9. Optional OLTP Databases.mp4 83.6 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/5. Getting Our Tools Ready.mp4 83.2 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/16. Improving Hyperparameters.mp4 83.1 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/18. Making Predictions.mp4 83.1 MB
  • 7. NumPy/4. NumPy DataTypes and Attributes.mp4 82.8 MB
  • 9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Classification Model 4 (Confusion Matrix).mp4 81.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.mp4 78.8 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.mp4 78.3 MB
  • 18. Learn Python/10. Numbers.mp4 76.2 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/10. Preparing Our Data For Machine Learning.mp4 76.1 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/17. Evaluating Our Model.mp4 75.1 MB
  • 7. NumPy/7. Viewing Arrays and Matrices.mp4 74.1 MB
  • 9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Regression Model 1 (R2 Score).mp4 73.8 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/6. Histograms And Subplots.mp4 73.1 MB
  • 18. Learn Python/26. Built-In Functions + Methods.mp4 72.8 MB
  • 7. NumPy/9. Manipulating Arrays 2.mp4 71.2 MB
  • 5. Data Science Environment Setup/10. Jupyter Notebook Walkthrough.mp4 70.6 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/5. Scatter Plot And Bar Plot.mp4 70.3 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/10. Filling Missing Categorical Values.mp4 70.2 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/6. Exploring Our Data.mp4 70.1 MB
  • 6. Pandas Data Analysis/13. How To Download The Course Assignments.mp4 70.0 MB
  • 7. NumPy/5. Creating NumPy Arrays.mp4 70.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/20. Making Predictions With Our Model.mp4 69.7 MB
  • 9. Scikit-learn Creating Machine Learning Models/26. Evaluating A Classification Model 2 (ROC Curve).mp4 69.2 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/19. Evaluating Our Model 3.mp4 68.0 MB
  • 18. Learn Python/48. Sets 2.mp4 67.4 MB
  • 18. Learn Python/3. How To Run Python Code.mp4 67.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/9. Getting Your Data Ready Splitting Your Data.mp4 66.8 MB
  • 9. Scikit-learn Creating Machine Learning Models/29. Evaluating A Classification Model 5 (Confusion Matrix).mp4 66.7 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/7. Finding Patterns.mp4 66.4 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/16. Tuning Hyperparameters 3.mp4 66.1 MB
  • 18. Learn Python/34. List Methods.mp4 64.8 MB
  • 3. Machine Learning and Data Science Framework/4. Types of Machine Learning Problems.mp4 63.4 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/9. Plotting From Pandas DataFrames.mp4 63.3 MB
  • 18. Learn Python/12. DEVELOPER FUNDAMENTALS I.mp4 62.6 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.mp4 59.7 MB
  • 9. Scikit-learn Creating Machine Learning Models/43. Saving And Loading A Model 2.mp4 59.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/19. Fitting A Model To The Data.mp4 59.3 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/11. Fitting A Machine Learning Model.mp4 58.2 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/12. Experimenting With Machine Learning Models.mp4 58.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Regression Model 3 (MSE).mp4 57.6 MB
  • 9. Scikit-learn Creating Machine Learning Models/21. predict() vs predict_proba().mp4 57.0 MB
  • 7. NumPy/11. Reshape and Transpose.mp4 56.1 MB
  • 9. Scikit-learn Creating Machine Learning Models/42. Saving And Loading A Model.mp4 55.2 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data 2.mp4 54.6 MB
  • 7. NumPy/6. NumPy Random Seed.mp4 54.4 MB
  • 7. NumPy/10. Standard Deviation and Variance.mp4 53.6 MB
  • 18. Learn Python/30. Exercise Password Checker.mp4 53.6 MB
  • 9. Scikit-learn Creating Machine Learning Models/27. Evaluating A Classification Model 3 (ROC Curve).mp4 53.1 MB
  • 18. Learn Python/28. Exercise Type Conversion.mp4 52.8 MB
  • 18. Learn Python/32. List Slicing.mp4 52.3 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/19. Saving And Sharing Your Plots.mp4 51.9 MB
  • 18. Learn Python/23. Formatted Strings.mp4 51.7 MB
  • 18. Learn Python/24. String Indexes.mp4 51.5 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/13. Plotting from Pandas DataFrames 4.mp4 51.4 MB
  • 5. Data Science Environment Setup/7. Windows Environment Setup.mp4 50.2 MB
  • 18. Learn Python/4. Our First Python Program.mp4 49.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/22. Making Predictions With Our Model (Regression).mp4 47.1 MB
  • 3. Machine Learning and Data Science Framework/11. Modelling - Comparison.mp4 47.1 MB
  • 2. Machine Learning 101/3. Exercise Machine Learning Playground.mp4 44.7 MB
  • 18. Learn Python/44. Dictionary Methods 2.mp4 44.4 MB
  • 13. Data Engineering/2. What Is Data.mp4 44.3 MB
  • 18. Learn Python/11. Math Functions.mp4 43.8 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/18. Evaluating Our Model 2.mp4 43.6 MB
  • 1. Introduction/1. Course Outline.mp4 42.7 MB
  • 9. Scikit-learn Creating Machine Learning Models/2. Scikit-learn Introduction.mp4 42.6 MB
  • 18. Learn Python/37. Common List Patterns.mp4 42.4 MB
  • 18. Learn Python/7. Learning Python.mp4 40.4 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/7. Subplots Option 2.mp4 39.9 MB
  • 5. Data Science Environment Setup/12. Jupyter Notebook Walkthrough 3.mp4 39.8 MB
  • 18. Learn Python/47. Sets.mp4 38.8 MB
  • 3. Machine Learning and Data Science Framework/7. Features In Data.mp4 38.6 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/2. Project Overview.mp4 36.1 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/2. Project Overview.mp4 34.5 MB
  • 7. NumPy/15. Sorting Arrays.mp4 34.4 MB
  • 18. Learn Python/40. Dictionaries.mp4 34.3 MB
  • 13. Data Engineering/7. Types Of Databases.mp4 34.1 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/2. Matplotlib Introduction.mp4 33.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/25. Evaluating A Classification Model 1 (Accuracy).mp4 32.9 MB
  • 18. Learn Python/19. Strings.mp4 32.5 MB
  • 5. Data Science Environment Setup/4. Conda Environments.mp4 32.0 MB
  • 2. Machine Learning 101/4. How Did We Get Here.mp4 32.0 MB
  • 3. Machine Learning and Data Science Framework/5. Types of Data.mp4 30.8 MB
  • 18. Learn Python/29. DEVELOPER FUNDAMENTALS II.mp4 30.7 MB
  • 18. Learn Python/8. Python Data Types.mp4 30.3 MB
  • 18. Learn Python/36. List Methods 3.mp4 29.0 MB
  • 3. Machine Learning and Data Science Framework/8. Modelling - Splitting Data.mp4 28.8 MB
  • 6. Pandas Data Analysis/3. Pandas Introduction.mp4 28.8 MB
  • 18. Learn Python/35. List Methods 2.mp4 28.7 MB
  • 3. Machine Learning and Data Science Framework/13. Tools We Will Use.mp4 28.7 MB
  • 18. Learn Python/43. Dictionary Methods.mp4 28.5 MB
  • 7. NumPy/2. NumPy Introduction.mp4 28.1 MB
  • 18. Learn Python/41. DEVELOPER FUNDAMENTALS III.mp4 27.9 MB
  • 7. NumPy/14. Comparison Operators.mp4 27.6 MB
  • 18. Learn Python/6. Exercise How Does Python Work.mp4 27.2 MB
  • 18. Learn Python/45. Tuples.mp4 26.9 MB
  • 2. Machine Learning 101/8. What Is Machine Learning Round 2.mp4 26.8 MB
  • 13. Data Engineering/5. What Is A Data Engineer 3.mp4 25.5 MB
  • 13. Data Engineering/4. What Is A Data Engineer 2.mp4 25.4 MB
  • 3. Machine Learning and Data Science Framework/3. 6 Step Machine Learning Framework.mp4 24.6 MB
  • 3. Machine Learning and Data Science Framework/9. Modelling - Picking the Model.mp4 24.4 MB
  • 18. Learn Python/22. Escape Sequences.mp4 24.3 MB
  • 2. Machine Learning 101/6. Types of Machine Learning.mp4 23.9 MB
  • 19. Learn Python Part 2/43. Exercise Comprehensions.mp4 23.0 MB
  • 18. Learn Python/31. Lists.mp4 23.0 MB
  • 18. Learn Python/15. Optional bin() and complex.mp4 23.0 MB
  • 19. Learn Python Part 2/30. Exercise Functions.mp4 22.9 MB
  • 3. Machine Learning and Data Science Framework/12. Experimentation.mp4 22.4 MB
  • 18. Learn Python/25. Immutability.mp4 21.8 MB
  • 18. Learn Python/42. Dictionary Keys.mp4 21.4 MB
  • 2. Machine Learning 101/2. AIMachine LearningData Science.mp4 20.6 MB
  • 2. Machine Learning 101/5. Exercise YouTube Recommendation Engine.mp4 20.4 MB
  • 5. Data Science Environment Setup/2. Introducing Our Tools.mp4 20.2 MB
  • 13. Data Engineering/13. Kafka and Stream Processing.mp4 20.2 MB
  • 18. Learn Python/33. Matrix.mp4 20.1 MB
  • 18. Learn Python/21. Type Conversion.mp4 19.9 MB
  • 3. Machine Learning and Data Science Framework/6. Types of Evaluation.mp4 18.6 MB
  • 18. Learn Python/46. Tuples 2.mp4 17.8 MB
  • 2. Machine Learning 101/1. What Is Machine Learning.mp4 17.7 MB
  • 18. Learn Python/27. Booleans.mp4 17.4 MB
  • 9. Scikit-learn Creating Machine Learning Models/10. Quick Tip Clean, Transform, Reduce.mp4 17.3 MB
  • 3. Machine Learning and Data Science Framework/10. Modelling - Tuning.mp4 16.8 MB
  • 17. Career Advice + Extra Bits/7. JTS Start With Why.mp4 16.2 MB
  • 18. Learn Python/18. Augmented Assignment Operator.mp4 16.1 MB
  • 13. Data Engineering/3. What Is A Data Engineer.mp4 15.9 MB
  • 13. Data Engineering/6. What Is A Data Engineer 4.mp4 15.7 MB
  • 18. Learn Python/13. Operator Precedence.mp4 15.1 MB
  • 18. Learn Python/38. List Unpacking.mp4 14.5 MB
  • 13. Data Engineering/1. Data Engineering Introduction.mp4 14.2 MB
  • 3. Machine Learning and Data Science Framework/1. Section Overview.mp4 14.0 MB
  • 7. NumPy/1. Section Overview.mp4 14.0 MB
  • 5. Data Science Environment Setup/3. What is Conda.mp4 13.1 MB
  • 9. Scikit-learn Creating Machine Learning Models/1. Section Overview.mp4 13.1 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/8. Quick Tip Data Visualizations.mp4 12.8 MB
  • 3. Machine Learning and Data Science Framework/2. Introducing Our Framework.mp4 11.9 MB
  • 17. Career Advice + Extra Bits/6. JTS Learn to Learn.mp4 11.7 MB
  • 21. Where To Go From Here/2. Thank You.mp4 11.7 MB
  • 18. Learn Python/17. Expressions vs Statements.mp4 11.5 MB
  • 6. Pandas Data Analysis/1. Section Overview.mp4 11.4 MB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/1. Section Overview.mp4 10.7 MB
  • 13. Data Engineering/11. Hadoop, HDFS and MapReduce.mp4 10.6 MB
  • 4. The 2 Paths/1. The 2 Paths.mp4 10.2 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/1. Section Overview.mp4 9.4 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/1. Section Overview.mp4 9.0 MB
  • 1. Introduction/4. Your First Day.mp4 8.6 MB
  • 18. Learn Python/39. None.mp4 8.3 MB
  • 18. Learn Python/20. String Concatenation.mp4 7.7 MB
  • 7. NumPy/16.2 numpy-images.zip.zip 7.6 MB
  • 13. Data Engineering/12. Apache Spark and Apache Flink.mp4 6.0 MB
  • 2. Machine Learning 101/9. Section Review.mp4 2.6 MB
  • 5. Data Science Environment Setup/1. Section Overview.mp4 2.4 MB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/4.2 matplotlib-anatomy-of-a-plot-with-code.png.png 670.5 kB
  • 8. Matplotlib + Seaborn Plotting and Data Visualization/4.1 matplotlib-anatomy-of-a-plot.png.png 378.3 kB
  • 6. Pandas Data Analysis/10.1 pandas-anatomy-of-a-dataframe.png.png 341.2 kB
  • 6. Pandas Data Analysis/4.1 pandas-anatomy-of-a-dataframe.png.png 341.2 kB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/3. Project Environment Setup.mp4.jpg 219.7 kB
  • 5. Data Science Environment Setup/3.4 conda-cheatsheet.pdf.pdf 206.1 kB
  • 9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.srt 32.5 kB
  • 5. Data Science Environment Setup/8. Windows Environment Setup 2.srt 32.4 kB
  • 9. Scikit-learn Creating Machine Learning Models/38. Tuning Hyperparameters.srt 31.3 kB
  • 6. Pandas Data Analysis/9.1 car-sales-extended-missing-data.csv.csv 30.9 kB
  • 9. Scikit-learn Creating Machine Learning Models/44. Putting It All Together.srt 27.1 kB
  • 9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.srt 26.1 kB
  • 5. Data Science Environment Setup/5. Mac Environment Setup.srt 24.5 kB
  • 9. Scikit-learn Creating Machine Learning Models/13. Getting Your Data Ready Handling Missing Values With Scikit-learn.srt 23.7 kB
  • 9. Scikit-learn Creating Machine Learning Models/11. Getting Your Data Ready Convert Data To Numbers.srt 23.3 kB
  • 5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough 2.srt 23.0 kB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/20. Finding The Most Important Features.srt 22.9 kB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/8. Finding Patterns 2.srt 22.9 kB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Turning Data Into Numbers.srt 22.9 kB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Feature Engineering.srt 22.7 kB
  • 9. Scikit-learn Creating Machine Learning Models/14. Choosing The Right Model For Your Data.srt 21.9 kB
  • 17. Career Advice + Extra Bits/9. CWD Git + Github.srt 21.7 kB
  • 5. Data Science Environment Setup/6. Mac Environment Setup 2.srt 21.2 kB
  • 17. Career Advice + Extra Bits/3. What If I Don_t Have Enough Experience.srt 20.5 kB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/5. Exploring Our Data.srt 20.5 kB
  • 7. NumPy/4. NumPy DataTypes and Attributes.srt 19.7 kB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/9. Finding Patterns 3.srt 19.3 kB
  • 9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 3.srt 19.2 kB
  • 17. Career Advice + Extra Bits/10. CWD Git + Github 2.srt 18.7 kB
  • 6. Pandas Data Analysis/9. Manipulating Data.srt 18.5 kB
  • 9. Scikit-learn Creating Machine Learning Models/35. Evaluating A Model With Cross Validation and Scoring Parameter.srt 18.4 kB
  • 6. Pandas Data Analysis/8. Selecting and Viewing Data with Pandas Part 2.srt 18.4 kB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.srt 18.2 kB
  • 11. Milestone Project 1 Supervised Learning (Binary Classification)/13. TuningImproving Our Model.srt 18.1 kB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Feature Importance.srt 17.7 kB
  • 9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model 2 (Cross Validation).srt 17.7 kB
  • 17. Career Advice + Extra Bits/11. Contributing To Open Source.srt 17.5 kB
  • 9. Scikit-learn Creating Machine Learning Models/18. Choosing The Right Model For Your Data 3 (Classification).srt 17.5 kB
  • 9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters 2.srt 17.4 kB
  • 7. NumPy/13. Exercise Nut Butter Store Sales.srt 17.4 kB
  • 9. Scikit-learn Creating Machine Learning Models/12. Getting Your Data Ready Handling Missing Values With Pandas.srt 17.4 kB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Filling Missing Numerical Values.srt 17.3 kB
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