GetFreeCourses.Co-Udemy-Complete Machine Learning & Data Science Bootcamp 2021

磁力链接/BT种子名称

GetFreeCourses.Co-Udemy-Complete Machine Learning & Data Science Bootcamp 2021

磁力链接/BT种子简介

种子哈希：e0b1ed74f2bdbf840d2b0e10f33cdbe05aa5ab71
文件大小： 19.23G
已经下载：916次
下载速度：极快
收录时间：2021-04-27
最近下载：2024-11-18

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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
  • 16. Career Advice + Extra Bits/9. CWD Git + Github.mp4 184.7 MB
  • 9. Scikit-learn Creating Machine Learning Models/41. Tuning Hyperparameters.mp4 184.3 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/32. Training Your Deep Neural Network.mp4 174.7 MB
  • 16. 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)/8. Feature Engineering.mp4 166.9 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/34. Make And Transform Predictions.mp4 162.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/48. Putting It All Together.mp4 157.9 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/21. Turning Data Into Batches 2.mp4 156.6 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Turning Data Into Numbers.mp4 153.3 MB
  • 5. Data Science Environment Setup/5. Mac Environment Setup.mp4 151.4 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/37. Visualizing And Evaluate Model Predictions 2.mp4 150.8 MB
  • 9. Scikit-learn Creating Machine Learning Models/16. Choosing The Right Model For Your Data.mp4 150.2 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/21. Feature Importance.mp4 149.2 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/41. Making Predictions On Test Images.mp4 147.7 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/40. Training Model On Full Dataset.mp4 146.6 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Preproccessing Our Data.mp4 146.1 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/10. Finding Patterns 3.mp4 144.6 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data.mp4 144.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/15. 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
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/15. Preparing The Images.mp4 140.4 MB
  • 16. Career Advice + Extra Bits/11. Contributing To Open Source.mp4 136.6 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/35. Transform Predictions To Text.mp4 136.2 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/22. Finding The Most Important Features.mp4 133.7 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/39. Saving And Loading A Trained Model.mp4 133.2 MB
  • 5. Data Science Environment Setup/6. Mac Environment Setup 2.mp4 131.6 MB
  • 8. Matplotlib Plotting and Data Visualization/18. Customizing Your Plots 2.mp4 129.6 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/22. Visualizing Our Data.mp4 127.9 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/25. Building A Deep Learning Model.mp4 127.8 MB
  • 9. Scikit-learn Creating Machine Learning Models/43. Tuning Hyperparameters 3.mp4 127.7 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/42. Submitting Model to Kaggle.mp4 127.2 MB
  • 8. Matplotlib Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.mp4 125.6 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/36. Visualizing Model Predictions.mp4 125.1 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/43. Making Predictions On Our Images.mp4 125.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/20. Choosing The Right Model For Your Data 3 (Classification).mp4 124.6 MB
  • 16. Career Advice + Extra Bits/10. CWD Git + Github 2.mp4 124.1 MB
  • 9. Scikit-learn Creating Machine Learning Models/49. Putting It All Together 2.mp4 122.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/42. Tuning Hyperparameters 2.mp4 122.5 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/9. Importing TensorFlow 2.mp4 122.4 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/14. Loading Our Data Labels.mp4 120.4 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/38. Visualizing And Evaluate Model Predictions 3.mp4 118.7 MB
  • 16. Career Advice + Extra Bits/12. Contributing To Open Source 2.mp4 118.5 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/15. Tuning Hyperparameters.mp4 113.3 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/16. Turning Data Labels Into Numbers.mp4 112.7 MB
  • 6. Pandas Data Analysis/8. Selecting and Viewing Data with Pandas Part 2.mp4 111.7 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/10. Filling Missing Numerical Values.mp4 111.5 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/27. Building A Deep Learning Model 3.mp4 111.1 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/26. Building A Deep Learning Model 2.mp4 111.1 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/5. Step 1~4 Framework Setup.mp4 110.6 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/19. Preprocess Images 2.mp4 110.2 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
  • 17. Learn Python/1. What Is A Programming Language.mp4 109.9 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/16. Tuning Hyperparameters 2.mp4 109.2 MB
  • 5. Data Science Environment Setup/12. Jupyter Notebook Walkthrough 2.mp4 108.9 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/15. Custom Evaluation Function.mp4 108.4 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/14. TuningImproving Our Model.mp4 107.8 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/2. Deep Learning and Unstructured Data.mp4 107.0 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.mp4 106.2 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/3. Project Environment Setup.mp4 105.7 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/9. Finding Patterns 2.mp4 104.8 MB
  • 8. Matplotlib Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.mp4 103.6 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/12. Choosing The Right Models.mp4 101.1 MB
  • 9. Scikit-learn Creating Machine Learning Models/26. Evaluating A Machine Learning Model 2 (Cross Validation).mp4 100.6 MB
  • 6. Pandas Data Analysis/4. Series, Data Frames and CSVs.mp4 100.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/39. Evaluating A Model With Scikit-learn Functions.mp4 99.4 MB
  • 17. Learn Python/17. Variables.mp4 98.1 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/16. Reducing Data.mp4 98.0 MB
  • 8. Matplotlib Plotting and Data Visualization/17. Customizing Your Plots.mp4 96.7 MB
  • 9. Scikit-learn Creating Machine Learning Models/38. 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 95.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/40. Improving A Machine Learning Model.mp4 95.4 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/18. Preprocess Images.mp4 94.5 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/13. Optional Reloading Colab Notebook.mp4 93.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.mp4 92.6 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/20. Turning Data Into Batches.mp4 92.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Classification Model 6 (Classification Report).mp4 91.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/25. Evaluating A Machine Learning Model (Score).mp4 91.4 MB
  • 9. Scikit-learn Creating Machine Learning Models/17. Choosing The Right Model For Your Data 2 (Regression).mp4 91.2 MB
  • 6. Pandas Data Analysis/10. Manipulating Data 2.mp4 90.7 MB
  • 8. Matplotlib Plotting and Data Visualization/3. Importing And Using Matplotlib.mp4 90.6 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/28. Building A Deep Learning Model 4.mp4 90.5 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/23. 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)/17. RandomizedSearchCV.mp4 90.0 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/4. Step 1~4 Framework Setup.mp4 89.9 MB
  • 7. NumPy/12. Dot Product vs Element Wise.mp4 88.0 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Splitting Data.mp4 86.7 MB
  • 18. Learn Python Part 2/45. Modules in Python.mp4 86.2 MB
  • 8. Matplotlib Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.mp4 86.2 MB
  • 8. Matplotlib Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.mp4 86.0 MB
  • 7. NumPy/8. Manipulating Arrays.mp4 84.6 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/11. Using A GPU.mp4 84.5 MB
  • 13. Data Engineering/9. Optional OLTP Databases.mp4 83.6 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/6. Getting Our Tools Ready.mp4 83.2 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/30. Evaluating Our Model.mp4 83.2 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/18. Improving Hyperparameters.mp4 83.1 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/20. Making Predictions.mp4 83.1 MB
  • 7. NumPy/4. NumPy DataTypes and Attributes.mp4 82.8 MB
  • 17. Learn Python/2. Python Interpreter.mp4 81.8 MB
  • 9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Classification Model 4 (Confusion Matrix).mp4 81.5 MB
  • 1. Introduction/1. Course Outline.mp4 81.0 MB
  • 6. Pandas Data Analysis/6. Describing Data with Pandas.mp4 79.2 MB
  • 9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.mp4 78.8 MB
  • 8. Matplotlib Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.mp4 78.3 MB
  • 18. Learn Python Part 2/2. Conditional Logic.mp4 78.2 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/4. Setting Up Google Colab.mp4 77.8 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/33. Evaluating Performance With TensorBoard.mp4 77.8 MB
  • 17. Learn Python/11. Numbers.mp4 76.2 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/11. Preparing Our Data For Machine Learning.mp4 76.1 MB
  • 18. Learn Python Part 2/48. Packages in Python.mp4 75.9 MB
  • 6. Pandas Data Analysis/7. Selecting and Viewing Data with Pandas.mp4 75.9 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/19. Evaluating Our Model.mp4 75.1 MB
  • 5. Data Science Environment Setup/13. Jupyter Notebook Walkthrough 3.mp4 74.9 MB
  • 7. NumPy/7. Viewing Arrays and Matrices.mp4 74.1 MB
  • 9. Scikit-learn Creating Machine Learning Models/34. Evaluating A Regression Model 1 (R2 Score).mp4 73.8 MB
  • 8. Matplotlib Plotting and Data Visualization/6. Histograms And Subplots.mp4 73.1 MB
  • 17. Learn Python/6. Python 2 vs Python 3.mp4 72.9 MB
  • 17. Learn Python/27. Built-In Functions + Methods.mp4 72.8 MB
  • 7. NumPy/9. Manipulating Arrays 2.mp4 71.2 MB
  • 18. Learn Python Part 2/36. Pure Functions.mp4 70.6 MB
  • 5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough.mp4 70.6 MB
  • 8. Matplotlib Plotting and Data Visualization/5. Scatter Plot And Bar Plot.mp4 70.3 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/11. Filling Missing Categorical Values.mp4 70.2 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/7. 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/22. Making Predictions With Our Model.mp4 69.7 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/17. Creating Our Own Validation Set.mp4 69.7 MB
  • 9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Classification Model 2 (ROC Curve).mp4 69.2 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/21. Evaluating Our Model 3.mp4 68.0 MB
  • 17. Learn Python/49. Sets 2.mp4 67.4 MB
  • 9. Scikit-learn Creating Machine Learning Models/32. Evaluating A Classification Model 5 (Confusion Matrix).mp4 66.9 MB
  • 9. Scikit-learn Creating Machine Learning Models/9. Getting Your Data Ready Splitting Your Data.mp4 66.8 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/8. Finding Patterns.mp4 66.4 MB
  • 18. Learn Python Part 2/24. return.mp4 66.1 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/17. Tuning Hyperparameters 3.mp4 66.1 MB
  • 17. Learn Python/35. 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 Plotting and Data Visualization/9. Plotting From Pandas DataFrames.mp4 63.3 MB
  • 17. Learn Python/13. DEVELOPER FUNDAMENTALS I.mp4 62.6 MB
  • 8. Matplotlib Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.mp4 59.7 MB
  • 9. Scikit-learn Creating Machine Learning Models/47. Saving And Loading A Model 2.mp4 59.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/21. Fitting A Model To The Data.mp4 59.3 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/12. Fitting A Machine Learning Model.mp4 58.2 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/13. Experimenting With Machine Learning Models.mp4 58.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Regression Model 3 (MSE).mp4 57.6 MB
  • 9. Scikit-learn Creating Machine Learning Models/23. predict() vs predict_proba().mp4 57.0 MB
  • 7. NumPy/11. Reshape and Transpose.mp4 56.1 MB
  • 18. Learn Python Part 2/41. List Comprehensions.mp4 55.9 MB
  • 18. Learn Python Part 2/47. Optional PyCharm.mp4 55.6 MB
  • 17. Learn Python/3. How To Run Python Code.mp4 55.4 MB
  • 9. Scikit-learn Creating Machine Learning Models/46. Saving And Loading A Model.mp4 55.2 MB
  • 18. Learn Python Part 2/40. reduce().mp4 54.8 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Exploring Our Data 2.mp4 54.6 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/6. Uploading Project Data.mp4 54.5 MB
  • 7. NumPy/6. NumPy Random Seed.mp4 54.5 MB
  • 7. NumPy/10. Standard Deviation and Variance.mp4 53.7 MB
  • 17. Learn Python/31. Exercise Password Checker.mp4 53.6 MB
  • 9. Scikit-learn Creating Machine Learning Models/29. Evaluating A Classification Model 3 (ROC Curve).mp4 53.1 MB
  • 17. Learn Python/29. Exercise Type Conversion.mp4 52.8 MB
  • 18. Learn Python Part 2/19. DEVELOPER FUNDAMENTALS IV.mp4 52.7 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/23. Preparing Our Inputs and Outputs.mp4 52.5 MB
  • 17. Learn Python/33. List Slicing.mp4 52.3 MB
  • 18. Learn Python Part 2/18. Our First GUI.mp4 52.1 MB
  • 8. Matplotlib Plotting and Data Visualization/19. Saving And Sharing Your Plots.mp4 51.9 MB
  • 17. Learn Python/24. Formatted Strings.mp4 51.7 MB
  • 17. Learn Python/25. String Indexes.mp4 51.6 MB
  • 8. Matplotlib Plotting and Data Visualization/13. Plotting from Pandas DataFrames 4.mp4 51.4 MB
  • 18. Learn Python Part 2/21. Functions.mp4 51.0 MB
  • 18. Learn Python Part 2/49. Different Ways To Import.mp4 50.3 MB
  • 5. Data Science Environment Setup/7. Windows Environment Setup.mp4 50.3 MB
  • 17. Learn Python/4. Our First Python Program.mp4 49.5 MB
  • 18. Learn Python Part 2/8. Exercise Logical Operators.mp4 48.9 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/12. Optional GPU and Google Colab.mp4 48.1 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/29. Summarizing Our Model.mp4 47.6 MB
  • 9. Scikit-learn Creating Machine Learning Models/24. Making Predictions With Our Model (Regression).mp4 47.1 MB
  • 3. Machine Learning and Data Science Framework/11. Modelling - Comparison.mp4 47.1 MB
  • 18. Learn Python Part 2/11. Iterables.mp4 45.3 MB
  • 18. Learn Python Part 2/29. args and kwargs.mp4 45.1 MB
  • 18. Learn Python Part 2/4. Truthy vs Falsey.mp4 44.9 MB
  • 2. Machine Learning 101/3. Exercise Machine Learning Playground.mp4 44.7 MB
  • 17. Learn Python/45. Dictionary Methods 2.mp4 44.4 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/7. Setting Up Our Data.mp4 44.3 MB
  • 13. Data Engineering/2. What Is Data.mp4 44.3 MB
  • 17. Learn Python/12. Math Functions.mp4 43.8 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/20. Evaluating Our Model 2.mp4 43.6 MB
  • 9. Scikit-learn Creating Machine Learning Models/2. Scikit-learn Introduction.mp4 42.6 MB
  • 17. Learn Python/38. Common List Patterns.mp4 42.4 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/5. Google Colab Workspace.mp4 41.6 MB
  • 17. Learn Python/8. Learning Python.mp4 40.4 MB
  • 18. Learn Python Part 2/37. map().mp4 40.3 MB
  • 18. Learn Python Part 2/23. Default Parameters and Keyword Arguments.mp4 40.0 MB
  • 8. Matplotlib Plotting and Data Visualization/7. Subplots Option 2.mp4 39.9 MB
  • 18. Learn Python Part 2/32. Scope Rules.mp4 39.5 MB
  • 17. Learn Python/48. Sets.mp4 38.8 MB
  • 3. Machine Learning and Data Science Framework/7. Features In Data.mp4 38.6 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/31. Preventing Overfitting.mp4 38.3 MB
  • 18. Learn Python Part 2/33. global Keyword.mp4 38.3 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/4. Optional Windows Project Environment Setup.mp4 37.6 MB
  • 18. Learn Python Part 2/42. Set Comprehensions.mp4 37.1 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/2. Project Overview.mp4 36.1 MB
  • 18. Learn Python Part 2/10. For Loops.mp4 36.0 MB
  • 18. Learn Python Part 2/9. is vs ==.mp4 35.2 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/2. Project Overview.mp4 34.6 MB
  • 7. NumPy/15. Sorting Arrays.mp4 34.4 MB
  • 17. Learn Python/41. Dictionaries.mp4 34.3 MB
  • 13. Data Engineering/7. Types Of Databases.mp4 34.1 MB
  • 8. Matplotlib Plotting and Data Visualization/2. Matplotlib Introduction.mp4 33.1 MB
  • 9. Scikit-learn Creating Machine Learning Models/27. Evaluating A Classification Model 1 (Accuracy).mp4 32.9 MB
  • 17. Learn Python/20. Strings.mp4 32.5 MB
  • 18. Learn Python Part 2/26. Methods vs Functions.mp4 32.2 MB
  • 5. Data Science Environment Setup/4. Conda Environments.mp4 32.1 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
  • 17. Learn Python/30. DEVELOPER FUNDAMENTALS II.mp4 30.7 MB
  • 17. Learn Python/9. Python Data Types.mp4 30.3 MB
  • 9. Scikit-learn Creating Machine Learning Models/35. Evaluating A Regression Model 2 (MAE).mp4 29.9 MB
  • 18. Learn Python Part 2/7. Logical Operators.mp4 29.7 MB
  • 18. Learn Python Part 2/13. range().mp4 29.7 MB
  • 18. Learn Python Part 2/15. While Loops.mp4 29.7 MB
  • 2. Machine Learning 101/1. What Is Machine Learning.mp4 29.7 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/10. Optional TensorFlow 2.0 Default Issue.mp4 29.5 MB
  • 18. Learn Python Part 2/3. Indentation In Python.mp4 29.4 MB
  • 1. Introduction/4. Your First Day.mp4 29.3 MB
  • 17. Learn Python/37. List Methods 3.mp4 29.0 MB
  • 3. Machine Learning and Data Science Framework/8. Modelling - Splitting Data.mp4 28.9 MB
  • 6. Pandas Data Analysis/3. Pandas Introduction.mp4 28.8 MB
  • 17. Learn Python/36. List Methods 2.mp4 28.7 MB
  • 3. Machine Learning and Data Science Framework/14. Tools We Will Use.mp4 28.7 MB
  • 17. Learn Python/44. Dictionary Methods.mp4 28.5 MB
  • 7. NumPy/2. NumPy Introduction.mp4 28.2 MB
  • 17. Learn Python/42. DEVELOPER FUNDAMENTALS III.mp4 27.9 MB
  • 7. NumPy/14. Comparison Operators.mp4 27.6 MB
  • 17. Learn Python/7. Exercise How Does Python Work.mp4 27.2 MB
  • 18. Learn Python Part 2/16. While Loops 2.mp4 27.2 MB
  • 17. Learn Python/46. Tuples.mp4 26.9 MB
  • 2. Machine Learning 101/8. What Is Machine Learning Round 2.mp4 26.8 MB
  • 18. Learn Python Part 2/14. enumerate().mp4 26.0 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
  • 15. Storytelling + Communication How To Present Your Work/5. Weekend Project Principle.mp4 24.7 MB
  • 18. Learn Python Part 2/38. filter().mp4 24.7 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
  • 17. Learn Python/23. Escape Sequences.mp4 24.3 MB
  • 18. Learn Python Part 2/22. Parameters and Arguments.mp4 24.3 MB
  • 2. Machine Learning 101/6. Types of Machine Learning.mp4 23.9 MB
  • 18. Learn Python Part 2/17. break, continue, pass.mp4 23.3 MB
  • 18. Learn Python Part 2/43. Exercise Comprehensions.mp4 23.0 MB
  • 17. Learn Python/32. Lists.mp4 23.0 MB
  • 17. Learn Python/16. Optional bin() and complex.mp4 23.0 MB
  • 18. Learn Python Part 2/30. Exercise Functions.mp4 22.9 MB
  • 3. Machine Learning and Data Science Framework/13. Experimentation.mp4 22.4 MB
  • 18. Learn Python Part 2/39. zip().mp4 22.3 MB
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/8. Setting Up Our Data 2.mp4 21.9 MB
  • 17. Learn Python/26. Immutability.mp4 21.8 MB
  • 17. Learn Python/43. Dictionary Keys.mp4 21.4 MB
  • 18. Learn Python Part 2/1. Breaking The Flow.mp4 21.3 MB
  • 18. Learn Python Part 2/20. Exercise Find Duplicates.mp4 21.2 MB
  • 15. Storytelling + Communication How To Present Your Work/2. Communicating Your Work.mp4 21.2 MB
  • 18. Learn Python Part 2/31. Scope.mp4 21.1 MB
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  • 15. Storytelling + Communication How To Present Your Work/6.1 Devblog by Hashnode (an easy and free way to create a blog you own).html 89 Bytes
  • 2. Machine Learning 101/5.1 Machine Learning Playground.html 88 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/25.1 PyTorch Hub (PyTorch version of TensorFlow Hub).html 85 Bytes
  • 17. Learn Python/2.1 python.org.html 84 Bytes
  • 7. NumPy/2.2 NumPy Documentation.html 83 Bytes
  • 17. Learn Python/3.1 Glot.io.html 77 Bytes
  • 17. Learn Python/3.2 Repl.it.html 77 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/10.1 Loading TensorFlow 2.0 into a Colab Notebook (if it isn't the default).html 0 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/14.1 Documentation on how many images Google recommends for image problems.html 0 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/17.1 Blog post by Rachel Thomas (of fast.ai) on how and why you should create a validation set.html 0 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/18.1 TensorFlow guidelines for loading all kinds of data (turning your data into Tensors).html 0 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/23.1 TensorFlow Hub (resource for pre-trained deep learning models and more).html 0 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/24. Optional How machines learn and what's going on behind the scenes.html 0 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/25.4 TensorFlow Hub (resource for pre-trained deep learning models and more).html 0 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/25.5 Papers with Code (a great resource for some of the best machine learning papers with code examples).html 0 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/27.1 Step by step breakdown of a convolutional neural network (what MobileNetV2 is made of).html 0 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/27.2 MobileNetV2 (the model we're using) architecture explanation by Sik-Ho Tsang.html 0 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/28.1 [Article] How to choose loss & activation functions when building a deep learning model.html 0 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/31.1 Early Stopping Callback (a way to stop your model from training when it stops improving) Documentation.html 0 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/4.1 Kaggle Dog Breed Identification Competition (the basis of our upcoming project).html 0 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/4.2 Google Colab IO example (how to get data in and out of your Colab notebook).html 0 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/4.3 End-to-end Dog Vision Notebook (the project we'll be working through).html 0 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/42.1 Dog Vision Predictions with MobileNetV2 Ready for Kaggle Submission.html 0 Bytes
  • 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/6.1 Google Colab IO example (how to get data in and out of your Colab notebook).html 0 Bytes
  • 15. Storytelling + Communication How To Present Your Work/6.2 fast_template by fast.ai (a template you can use for your blog on GitHub Pages).html 0 Bytes
  • 5. Data Science Environment Setup/3.4 Getting your computer ready for machine learning How, what and why you should use Anaconda, Miniconda and Conda (blog post).html 0 Bytes

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