[FreeAllCourse.Com] Udemy - Complete Machine Learning and Data Science Zero to Mastery - 磁力管家

BT种子名称

分享给好友

BT种子基本信息

种子哈希：efb18a1509c7236abbca990bc7b38e5c3269f8d0
文档大小：20.6 GB
文档个数：821个文档
下载次数：546次
下载速度：极快
收录时间：2021-03-18
最近下载：2025-05-04
DMCA/屏蔽：DMCA/屏蔽

下载磁力链接

magnet:?xt=urn:btih:EFB18A1509C7236ABBCA990BC7B38E5C3269F8D0
复制磁力链接到utorrent、Bitcomet、迅雷、115、百度网盘等下载工具进行下载。

下载BT种子

磁力链接种子下载迅雷下载二维码迅雷看看
磁力链接在线播放？试试百度云网盘离线下载播放！

[FreeAllCourse.Com] Udemy - Complete Machine Learning and Data Science Zero to Mastery的二维码

文档列表

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/39. Tuning Hyperparameters.mp4 184.1 MB
14. Neural Networks Deep Learning/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)/7. Feature Engineering.mp4 166.9 MB
9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together.mp4 166.0 MB
14. Neural Networks Deep Learning/34. Make And Transform Predictions.mp4 162.5 MB
14. Neural Networks Deep Learning/21. Turning Data Into Batches 2.mp4 156.6 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
14. Neural Networks Deep Learning/37. Visualizing And Evaluate Model Predictions 2.mp4 150.8 MB
9. Scikit-learn Creating Machine Learning Models/15. 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
14. Neural Networks Deep Learning/41. Making Predictions On Test Images.mp4 147.7 MB
14. Neural Networks Deep Learning/40. Training Model On Full Dataset.mp4 146.6 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.mp4 146.1 MB
11. Milestone Project 1 Supervised Learning (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/14. 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/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/35. Transform Predictions To Text.mp4 136.2 MB
11. Milestone Project 1 Supervised Learning (Classification)/20. Finding The Most Important Features.mp4 133.7 MB
14. Neural Networks Deep Learning/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/22. Visualizing Our Data.mp4 127.9 MB
14. Neural Networks Deep Learning/25. Building A Deep Learning Model.mp4 127.8 MB
9. Scikit-learn Creating Machine Learning Models/41. Tuning Hyperparameters 3.mp4 127.7 MB
14. Neural Networks Deep Learning/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/36. Visualizing Model Predictions.mp4 125.1 MB
14. Neural Networks Deep Learning/43. Making Predictions On Our Images.mp4 125.0 MB
9. Scikit-learn Creating Machine Learning Models/19. 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/46. Putting It All Together 2.mp4 122.5 MB
9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 2.mp4 122.4 MB
14. Neural Networks Deep Learning/9. Importing TensorFlow 2.mp4 122.4 MB
14. Neural Networks Deep Learning/14. Loading Our Data Labels.mp4 120.4 MB
14. Neural Networks Deep Learning/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)/14. Tuning Hyperparameters.mp4 113.2 MB
14. Neural Networks Deep Learning/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)/9. Filling Missing Numerical Values.mp4 111.5 MB
14. Neural Networks Deep Learning/27. Building A Deep Learning Model 3.mp4 111.1 MB
14. Neural Networks Deep Learning/26. Building A Deep Learning Model 2.mp4 111.0 MB
11. Milestone Project 1 Supervised Learning (Classification)/4. Step 1~4 Framework Setup.mp4 110.6 MB
14. Neural Networks Deep Learning/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)/15. 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)/13. Custom Evaluation Function.mp4 108.4 MB
11. Milestone Project 1 Supervised Learning (Classification)/13. TuningImproving Our Model.mp4 107.8 MB
14. Neural Networks Deep Learning/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)/8. 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)/11. Choosing The Right Models.mp4 101.1 MB
9. Scikit-learn Creating Machine Learning Models/25. 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/37. Evaluating A Model With Scikit-learn Functions.mp4 99.4 MB
17. Learn Python/16. Variables.mp4 98.1 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Reducing Data.mp4 98.0 MB
17. Learn Python/2. Python Interpreter.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/36. 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/38. Improving A Machine Learning Model.mp4 95.4 MB
14. Neural Networks Deep Learning/18. Preprocess Images.mp4 94.5 MB
14. Neural Networks Deep Learning/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/20. Turning Data Into Batches.mp4 92.0 MB
9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Classification Model 6 (Classification Report).mp4 91.5 MB
9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model (Score).mp4 91.4 MB
9. Scikit-learn Creating Machine Learning Models/16. 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 Plotting and Data Visualization/3. Importing And Using Matplotlib.mp4 90.6 MB
14. Neural Networks Deep Learning/28. Building A Deep Learning Model 4.mp4 90.5 MB
11. Milestone Project 1 Supervised Learning (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
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 86.1 MB
17. Learn Python/5. Python 2 vs Python 3.mp4 86.1 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/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)/5. Getting Our Tools Ready.mp4 83.2 MB
14. Neural Networks Deep Learning/30. Evaluating Our Model.mp4 83.1 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/29. 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/4. Setting Up Google Colab.mp4 77.8 MB
14. Neural Networks Deep Learning/33. Evaluating Performance With TensorBoard.mp4 77.8 MB
17. Learn Python/10. Numbers.mp4 76.2 MB
11. Milestone Project 1 Supervised Learning (Classification)/10. 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)/17. 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/32. 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/26. 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)/10. Filling Missing Categorical Values.mp4 70.2 MB
11. Milestone Project 1 Supervised Learning (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/21. Making Predictions With Our Model.mp4 69.7 MB
14. Neural Networks Deep Learning/17. Creating Our Own Validation Set.mp4 69.7 MB
9. Scikit-learn Creating Machine Learning Models/27. Evaluating A Classification Model 2 (ROC Curve).mp4 69.2 MB
11. Milestone Project 1 Supervised Learning (Classification)/19. Evaluating Our Model 3.mp4 68.0 MB
17. Learn Python/48. Sets 2.mp4 67.4 MB
17. 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/30. Evaluating A Classification Model 5 (Confusion Matrix).mp4 66.7 MB
11. Milestone Project 1 Supervised Learning (Classification)/7. Finding Patterns.mp4 66.4 MB
18. Learn Python Part 2/24. return.mp4 66.1 MB
11. Milestone Project 1 Supervised Learning (Classification)/16. Tuning Hyperparameters 3.mp4 66.1 MB
17. 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 Plotting and Data Visualization/9. Plotting From Pandas DataFrames.mp4 63.3 MB
17. Learn Python/12. 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/44. Saving And Loading A Model 2.mp4 59.5 MB
9. Scikit-learn Creating Machine Learning Models/20. 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 (Classification)/12. Experimenting With Machine Learning Models.mp4 58.0 MB
9. Scikit-learn Creating Machine Learning Models/34. Evaluating A Regression Model 3 (MSE).mp4 57.6 MB
9. Scikit-learn Creating Machine Learning Models/22. 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
9. Scikit-learn Creating Machine Learning Models/43. 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)/6. Exploring Our Data 2.mp4 54.6 MB
14. Neural Networks Deep Learning/6. Uploading Project Data.mp4 54.5 MB
7. NumPy/6. NumPy Random Seed.mp4 54.4 MB
7. NumPy/10. Standard Deviation and Variance.mp4 53.6 MB
17. Learn Python/30. Exercise Password Checker.mp4 53.6 MB
9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Classification Model 3 (ROC Curve).mp4 53.1 MB
17. Learn Python/28. 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/23. Preparing Our Inputs and Outputs.mp4 52.5 MB
17. Learn Python/32. List Slicing.mp4 52.3 MB
18. Learn Python Part 2/18. Our First GUI.mp4 52.0 MB
8. Matplotlib Plotting and Data Visualization/19. Saving And Sharing Your Plots.mp4 51.9 MB
17. Learn Python/23. Formatted Strings.mp4 51.6 MB
17. Learn Python/24. String Indexes.mp4 51.5 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 50.2 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/12. Optional GPU and Google Colab.mp4 48.1 MB
14. Neural Networks Deep Learning/29. Summarizing Our Model.mp4 47.6 MB
9. Scikit-learn Creating Machine Learning Models/23. 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/44. Dictionary Methods 2.mp4 44.4 MB
14. Neural Networks Deep Learning/7. Setting Up Our Data.mp4 44.3 MB
13. Data Engineering/2. What Is Data.mp4 44.3 MB
17. Learn Python/11. Math Functions.mp4 43.8 MB
11. Milestone Project 1 Supervised Learning (Classification)/18. 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/37. Common List Patterns.mp4 42.4 MB
14. Neural Networks Deep Learning/5. Google Colab Workspace.mp4 41.6 MB
17. Learn Python/7. Learning Python.mp4 40.4 MB
18. Learn Python Part 2/37. map().mp4 40.2 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/47. 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/31. Preventing Overfitting.mp4 38.3 MB
18. Learn Python Part 2/33. global Keyword.mp4 38.3 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 34.5 MB
7. NumPy/15. Sorting Arrays.mp4 34.4 MB
17. Learn Python/40. 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 33.0 MB
9. Scikit-learn Creating Machine Learning Models/26. Evaluating A Classification Model 1 (Accuracy).mp4 32.9 MB
17. Learn Python/19. 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 32.0 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 30.7 MB
17. Learn Python/29. DEVELOPER FUNDAMENTALS II.mp4 30.7 MB
17. Learn Python/8. Python Data Types.mp4 30.3 MB
9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Regression Model 2 (MAE).mp4 29.9 MB
18. Learn Python Part 2/13. range().mp4 29.7 MB
18. Learn Python Part 2/7. Logical Operators.mp4 29.7 MB
2. Machine Learning 101/1. What Is Machine Learning.mp4 29.7 MB
18. Learn Python Part 2/15. While Loops.mp4 29.7 MB
14. Neural Networks Deep Learning/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/36. 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/35. List Methods 2.mp4 28.7 MB
3. Machine Learning and Data Science Framework/13. Tools We Will Use.mp4 28.7 MB
17. Learn Python/43. Dictionary Methods.mp4 28.5 MB
7. NumPy/2. NumPy Introduction.mp4 28.1 MB
17. Learn Python/41. DEVELOPER FUNDAMENTALS III.mp4 27.9 MB
7. NumPy/14. Comparison Operators.mp4 27.6 MB
17. Learn Python/6. 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/45. Tuples.mp4 26.9 MB
2. Machine Learning 101/8. What Is Machine Learning Round 2.mp4 26.7 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/22. 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/31. Lists.mp4 23.0 MB
17. Learn Python/15. 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/12. Experimentation.mp4 22.4 MB
18. Learn Python Part 2/39. zip().mp4 22.3 MB
14. Neural Networks Deep Learning/8. Setting Up Our Data 2.mp4 21.9 MB
17. Learn Python/25. Immutability.mp4 21.8 MB
17. Learn Python/42. 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
18. Learn Python Part 2/5. Ternary Operator.mp4 20.7 MB
2. Machine Learning 101/2. AIMachine LearningData Science.mp4 20.6 MB
18. Learn Python Part 2/28. Clean Code.mp4 20.6 MB
2. Machine Learning 101/5. Exercise YouTube Recommendation Engine.mp4 20.4 MB
18. Learn Python Part 2/6. Short Circuiting.mp4 20.3 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 Part 2/35. Why Do We Need Scope.mp4 20.1 MB
17. Learn Python/33. Matrix.mp4 20.1 MB
17. Learn Python/21. Type Conversion.mp4 19.9 MB
15. Storytelling + Communication How To Present Your Work/4. Communicating With Co-Workers.mp4 19.9 MB
15. Storytelling + Communication How To Present Your Work/3. Communicating With Managers.mp4 19.3 MB
18. Learn Python Part 2/34. nonlocal Keyword.mp4 19.1 MB
3. Machine Learning and Data Science Framework/6. Types of Evaluation.mp4 18.6 MB
18. Learn Python Part 2/27. Docstrings.mp4 18.2 MB
17. Learn Python/46. Tuples 2.mp4 17.8 MB
9. Scikit-learn Creating Machine Learning Models/42. Quick Tip Correlation Analysis.mp4 17.7 MB
17. 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
18. Learn Python Part 2/12. Exercise Tricky Counter.mp4 17.2 MB
3. Machine Learning and Data Science Framework/10. Modelling - Tuning.mp4 16.8 MB
16. Career Advice + Extra Bits/7. JTS Start With Why.mp4 16.2 MB
17. 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
15. Storytelling + Communication How To Present Your Work/6. Communicating With Outside World.mp4 15.2 MB
17. Learn Python/13. Operator Precedence.mp4 15.1 MB
17. 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 Plotting and Data Visualization/8. Quick Tip Data Visualizations.mp4 12.9 MB
14. Neural Networks Deep Learning/1. Section Overview.mp4 12.8 MB
15. Storytelling + Communication How To Present Your Work/7. Storytelling.mp4 12.6 MB
3. Machine Learning and Data Science Framework/2. Introducing Our Framework.mp4 11.9 MB
16. Career Advice + Extra Bits/6. JTS Learn to Learn.mp4 11.7 MB
20. Where To Go From Here/2. Thank You.mp4 11.7 MB
9. Scikit-learn Creating Machine Learning Models/18. Quick Tip How ML Algorithms Work.mp4 11.6 MB
17. Learn Python/17. Expressions vs Statements.mp4 11.5 MB
15. Storytelling + Communication How To Present Your Work/1. Section Overview.mp4 11.5 MB
6. Pandas Data Analysis/1. Section Overview.mp4 11.4 MB
11. Milestone Project 1 Supervised Learning (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 Plotting and Data Visualization/1. Section Overview.mp4 9.0 MB
17. Learn Python/39. None.mp4 8.3 MB
17. Learn Python/20. String Concatenation.mp4 7.7 MB
7. NumPy/16.1 numpy-images.zip 7.6 MB
5. Data Science Environment Setup/1. Section Overview.mp4 6.3 MB
13. Data Engineering/12. Apache Spark and Apache Flink.mp4 6.0 MB
2. Machine Learning 101/9. Section Review.mp4 5.8 MB
8. Matplotlib Plotting and Data Visualization/4.2 matplotlib-anatomy-of-a-plot-with-code.png 670.5 kB
8. Matplotlib Plotting and Data Visualization/4.1 matplotlib-anatomy-of-a-plot.png 378.3 kB
6. Pandas Data Analysis/10.1 pandas-anatomy-of-a-dataframe.png 341.2 kB
6. Pandas Data Analysis/4.1 pandas-anatomy-of-a-dataframe.png 341.2 kB
5. Data Science Environment Setup/11.1 6-step-ml-framework.png 332.0 kB
5. Data Science Environment Setup/3.2 conda-cheatsheet.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/39. Tuning Hyperparameters.srt 31.3 kB
9. Scikit-learn Creating Machine Learning Models/45. 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/14. Getting Your Data Ready Handling Missing Values With Scikit-learn.srt 23.7 kB
14. Neural Networks Deep Learning/32. Training Your Deep Neural Network.srt 23.6 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/12. Jupyter Notebook Walkthrough 2.srt 23.0 kB
11. Milestone Project 1 Supervised Learning (Classification)/20. Finding The Most Important Features.srt 22.9 kB
11. Milestone Project 1 Supervised Learning (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/15. Choosing The Right Model For Your Data.srt 21.9 kB
16. Career Advice + Extra Bits/9. CWD Git + Github.srt 21.7 kB
9. Scikit-learn Creating Machine Learning Models/9.1 scikit-learn-data.zip 21.3 kB
5. Data Science Environment Setup/6. Mac Environment Setup 2.srt 21.2 kB
14. Neural Networks Deep Learning/41. Making Predictions On Test Images.srt 20.8 kB
14. Neural Networks Deep Learning/2. Deep Learning and Unstructured Data.srt 20.7 kB
14. Neural Networks Deep Learning/21. Turning Data Into Batches 2.srt 20.6 kB
16. 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
14. Neural Networks Deep Learning/34. Make And Transform Predictions.srt 19.6 kB
14. Neural Networks Deep Learning/40. Training Model On Full Dataset.srt 19.6 kB
11. Milestone Project 1 Supervised Learning (Classification)/9. Finding Patterns 3.srt 19.3 kB
9. Scikit-learn Creating Machine Learning Models/41. Tuning Hyperparameters 3.srt 19.2 kB
14. Neural Networks Deep Learning/43. Making Predictions On Our Images.srt 19.0 kB
16. 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/36. 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 (Classification)/13. TuningImproving Our Model.srt 18.1 kB
14. Neural Networks Deep Learning/37. Visualizing And Evaluate Model Predictions 2.srt 18.1 kB
14. Neural Networks Deep Learning/35. Transform Predictions To Text.srt 18.0 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Feature Importance.srt 17.7 kB
9. Scikit-learn Creating Machine Learning Models/25. Evaluating A Machine Learning Model 2 (Cross Validation).srt 17.7 kB
16. Career Advice + Extra Bits/11. Contributing To Open Source.srt 17.5 kB
9. Scikit-learn Creating Machine Learning Models/19. Choosing The Right Model For Your Data 3 (Classification).srt 17.5 kB
14. Neural Networks Deep Learning/36. Visualizing Model Predictions.srt 17.4 kB
9. Scikit-learn Creating Machine Learning Models/40. 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
14. Neural Networks Deep Learning/39. Saving And Loading A Trained Model.srt 17.3 kB
6. Pandas Data Analysis/4. Series, Data Frames and CSVs.srt 17.2 kB
14. Neural Networks Deep Learning/9. Importing TensorFlow 2.srt 17.2 kB
11. Milestone Project 1 Supervised Learning (Classification)/4. Step 1~4 Framework Setup.srt 17.0 kB
14. Neural Networks Deep Learning/42. Submitting Model to Kaggle.srt 17.0 kB
9. Scikit-learn Creating Machine Learning Models/37. Evaluating A Model With Scikit-learn Functions.srt 16.7 kB
7. NumPy/8. Manipulating Arrays.srt 16.6 kB
9. Scikit-learn Creating Machine Learning Models/46. Putting It All Together 2.srt 16.5 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Custom Evaluation Function.srt 16.5 kB
14. Neural Networks Deep Learning/14. Loading Our Data Labels.srt 16.5 kB
8. Matplotlib Plotting and Data Visualization/3. Importing And Using Matplotlib.srt 16.4 kB
17. Learn Python/16. Variables.srt 16.4 kB
14. Neural Networks Deep Learning/25. Building A Deep Learning Model.srt 16.3 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.srt 16.3 kB
11. Milestone Project 1 Supervised Learning (Classification)/14. Tuning Hyperparameters.srt 16.0 kB
18. Learn Python Part 2/2. Conditional Logic.srt 16.0 kB
14. Neural Networks Deep Learning/22. Visualizing Our Data.srt 16.0 kB
7. NumPy/12. Dot Product vs Element Wise.srt 15.7 kB
5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough.srt 15.5 kB
14. Neural Networks Deep Learning/15. Preparing The Images.srt 15.5 kB
11. Milestone Project 1 Supervised Learning (Classification)/17. Evaluating Our Model.srt 15.5 kB
9. Scikit-learn Creating Machine Learning Models/29. Evaluating A Classification Model 4 (Confusion Matrix).srt 15.5 kB
11. Milestone Project 1 Supervised Learning (Classification)/15. Tuning Hyperparameters 2.srt 15.5 kB
18. Learn Python Part 2/24. return.srt 15.3 kB
8. Matplotlib Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.srt 15.3 kB
9. Scikit-learn Creating Machine Learning Models/38. Improving A Machine Learning Model.srt 15.2 kB
8. Matplotlib Plotting and Data Visualization/5. Scatter Plot And Bar Plot.srt 15.0 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Reducing Data.srt 15.0 kB
6. Pandas Data Analysis/7. Selecting and Viewing Data with Pandas.srt 14.9 kB
9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Classification Model 6 (Classification Report).srt 14.9 kB
11. Milestone Project 1 Supervised Learning (Classification)/3. Project Environment Setup.srt 14.7 kB
8. Matplotlib Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.srt 14.5 kB
3. Machine Learning and Data Science Framework/4. Types of Machine Learning Problems.srt 14.3 kB
8. Matplotlib Plotting and Data Visualization/17. Customizing Your Plots.srt 14.3 kB
6. Pandas Data Analysis/10. Manipulating Data 2.srt 14.2 kB
14. Neural Networks Deep Learning/38. Visualizing And Evaluate Model Predictions 3.srt 14.1 kB
11. Milestone Project 1 Supervised Learning (Classification)/21. Reviewing The Project.srt 14.1 kB
14. Neural Networks Deep Learning/16. Turning Data Labels Into Numbers.srt 14.1 kB
6. Pandas Data Analysis/11. Manipulating Data 3.srt 14.0 kB
8. Matplotlib Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.srt 14.0 kB
6. Pandas Data Analysis/6. Describing Data with Pandas.srt 13.9 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/12. Splitting Data.srt 13.8 kB
11. Milestone Project 1 Supervised Learning (Classification)/7. Finding Patterns.srt 13.7 kB
8. Matplotlib Plotting and Data Visualization/18. Customizing Your Plots 2.srt 13.6 kB
3. Machine Learning and Data Science Framework/11. Modelling - Comparison.srt 13.4 kB
11. Milestone Project 1 Supervised Learning (Classification)/11. Choosing The Right Models.srt 13.3 kB
14. Neural Networks Deep Learning/18. Preprocess Images.srt 13.2 kB
14. Neural Networks Deep Learning/19. Preprocess Images 2.srt 13.2 kB
7. NumPy/7. Viewing Arrays and Matrices.srt 13.2 kB
9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model (Score).srt 13.2 kB
11. Milestone Project 1 Supervised Learning (Classification)/5. Getting Our Tools Ready.srt 13.1 kB
18. Learn Python Part 2/45. Modules in Python.srt 13.0 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/15. RandomizedSearchCV.srt 13.0 kB
14. Neural Networks Deep Learning/26. Building A Deep Learning Model 2.srt 12.8 kB
18. Learn Python Part 2/48. Packages in Python.srt 12.8 kB
8. Matplotlib Plotting and Data Visualization/6. Histograms And Subplots.srt 12.7 kB
7. NumPy/5. Creating NumPy Arrays.srt 12.7 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/4. Step 1~4 Framework Setup.srt 12.7 kB
9. Scikit-learn Creating Machine Learning Models/27. Evaluating A Classification Model 2 (ROC Curve).srt 12.6 kB
14. Neural Networks Deep Learning/11. Using A GPU.srt 12.4 kB
13. Data Engineering/9. Optional OLTP Databases.srt 12.4 kB
9. Scikit-learn Creating Machine Learning Models/21. Making Predictions With Our Model.srt 12.4 kB
9. Scikit-learn Creating Machine Learning Models/9. Getting Your Data Ready Splitting Your Data.srt 12.4 kB
14. Neural Networks Deep Learning/28. Building A Deep Learning Model 4.srt 12.3 kB
11. Milestone Project 1 Supervised Learning (Classification)/10. Preparing Our Data For Machine Learning.srt 12.3 kB
9. Scikit-learn Creating Machine Learning Models/32. Evaluating A Regression Model 1 (R2 Score).srt 12.3 kB
9. Scikit-learn Creating Machine Learning Models/16. Choosing The Right Model For Your Data 2 (Regression).srt 12.3 kB
8. Matplotlib Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.srt 11.9 kB
14. Neural Networks Deep Learning/20. Turning Data Into Batches.srt 11.9 kB
9. Scikit-learn Creating Machine Learning Models/22. predict() vs predict_proba().srt 11.8 kB
11. Milestone Project 1 Supervised Learning (Classification)/19. Evaluating Our Model 3.srt 11.8 kB
7. NumPy/9. Manipulating Arrays 2.srt 11.8 kB
5. Data Science Environment Setup/13. Jupyter Notebook Walkthrough 3.srt 11.8 kB
8. Matplotlib Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.srt 11.7 kB
11. Milestone Project 1 Supervised Learning (Classification)/6. Exploring Our Data.srt 11.7 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/18. Making Predictions.srt 11.6 kB
14. Neural Networks Deep Learning/17. Creating Our Own Validation Set.srt 11.6 kB
14. Neural Networks Deep Learning/27. Building A Deep Learning Model 3.srt 11.5 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/10. Filling Missing Categorical Values.srt 11.5 kB
9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 5 (Confusion Matrix).srt 11.5 kB
17. Learn Python/10. Numbers.srt 11.4 kB
8. Matplotlib Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.srt 11.3 kB
11. Milestone Project 1 Supervised Learning (Classification)/6.1 heart-disease.csv 11.3 kB
5. Data Science Environment Setup/11.3 heart-disease.csv 11.3 kB
8. Matplotlib Plotting and Data Visualization/13.1 heart-disease.csv 11.3 kB
6. Pandas Data Analysis/13. How To Download The Course Assignments.srt 11.3 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/16. Improving Hyperparameters.srt 11.3 kB
17. Learn Python/34. List Methods.srt 11.0 kB
9. Scikit-learn Creating Machine Learning Models/2. Scikit-learn Introduction.srt 10.9 kB
18. Learn Python Part 2/47. Optional PyCharm.srt 10.8 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/11. Fitting A Machine Learning Model.srt 10.7 kB
7. NumPy/16. Turn Images Into NumPy Arrays.srt 10.7 kB
14. Neural Networks Deep Learning/30. Evaluating Our Model.srt 10.7 kB
18. Learn Python Part 2/18. Our First GUI.srt 10.6 kB
17. Learn Python/26. Built-In Functions + Methods.srt 10.5 kB
16. Career Advice + Extra Bits/12. Contributing To Open Source 2.srt 10.4 kB
9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.srt 10.3 kB
18. Learn Python Part 2/36. Pure Functions.srt 10.3 kB
9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Classification Model 3 (ROC Curve).srt 10.3 kB
11. Milestone Project 1 Supervised Learning (Classification)/2. Project Overview.srt 10.3 kB
11. Milestone Project 1 Supervised Learning (Classification)/16. Tuning Hyperparameters 3.srt 10.2 kB
9. Scikit-learn Creating Machine Learning Models/43. Saving And Loading A Model.srt 10.1 kB
7. NumPy/6. NumPy Random Seed.srt 10.0 kB
14. Neural Networks Deep Learning/4. Setting Up Google Colab.srt 9.9 kB
11. Milestone Project 1 Supervised Learning (Classification)/12. Experimenting With Machine Learning Models.srt 9.9 kB
14. Neural Networks Deep Learning/33. Evaluating Performance With TensorBoard.srt 9.8 kB
7. NumPy/11. Reshape and Transpose.srt 9.8 kB
8. Matplotlib Plotting and Data Visualization/13. Plotting from Pandas DataFrames 4.srt 9.6 kB
18. Learn Python Part 2/41. List Comprehensions.srt 9.6 kB
7. NumPy/10. Standard Deviation and Variance.srt 9.6 kB
9. Scikit-learn Creating Machine Learning Models/20. Fitting A Model To The Data.srt 9.6 kB
17. Learn Python/48. Sets 2.srt 9.5 kB
9. Scikit-learn Creating Machine Learning Models/34. Evaluating A Regression Model 3 (MSE).srt 9.5 kB
17. Learn Python/24. String Indexes.srt 9.4 kB
18. Learn Python Part 2/21. Functions.srt 9.4 kB
1. Introduction/1. Course Outline.srt 9.4 kB
9. Scikit-learn Creating Machine Learning Models/23. Making Predictions With Our Model (Regression).srt 9.3 kB
17. Learn Python/4. Our First Python Program.srt 9.2 kB
8. Matplotlib Plotting and Data Visualization/9. Plotting From Pandas DataFrames.srt 9.2 kB
15. Storytelling + Communication How To Present Your Work/5. Weekend Project Principle.srt 9.2 kB
9. Scikit-learn Creating Machine Learning Models/44. Saving And Loading A Model 2.srt 9.2 kB
17. Learn Python/23. Formatted Strings.srt 9.0 kB
7. NumPy/15. Sorting Arrays.srt 9.0 kB
2. Machine Learning 101/1. What Is Machine Learning.srt 8.9 kB
14. Neural Networks Deep Learning/6. Uploading Project Data.srt 8.8 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data 2.srt 8.8 kB
17. Learn Python/28. Exercise Type Conversion.srt 8.8 kB
17. Learn Python/32. List Slicing.srt 8.7 kB
18. Learn Python Part 2/32. Scope Rules.srt 8.7 kB
17. Learn Python/47. Sets.srt 8.6 kB
18. Learn Python Part 2/8. Exercise Logical Operators.srt 8.6 kB
18. Learn Python Part 2/40. reduce().srt 8.6 kB
13. Data Engineering/7. Types Of Databases.srt 8.6 kB
17. Learn Python/2. Python Interpreter.srt 8.5 kB
17. Learn Python/5. Python 2 vs Python 3.srt 8.4 kB
18. Learn Python Part 2/9. is vs ==.srt 8.3 kB
18. Learn Python Part 2/7. Logical Operators.srt 8.3 kB
2. Machine Learning 101/3. Exercise Machine Learning Playground.srt 8.3 kB
18. Learn Python Part 2/29. args and kwargs.srt 8.3 kB
8. Matplotlib Plotting and Data Visualization/2. Matplotlib Introduction.srt 8.2 kB
17. Learn Python/30. Exercise Password Checker.srt 8.1 kB
18. Learn Python Part 2/19. DEVELOPER FUNDAMENTALS IV.srt 8.0 kB
14. Neural Networks Deep Learning/23. Preparing Our Inputs and Outputs.srt 8.0 kB
14. Neural Networks Deep Learning/13. Optional Reloading Colab Notebook.srt 8.0 kB
3. Machine Learning and Data Science Framework/8. Modelling - Splitting Data.srt 7.9 kB
5. Data Science Environment Setup/7. Windows Environment Setup.srt 7.8 kB
13. Data Engineering/2. What Is Data.srt 7.8 kB
18. Learn Python Part 2/10. For Loops.srt 7.7 kB
7. NumPy/2. NumPy Introduction.srt 7.7 kB
18. Learn Python Part 2/49. Different Ways To Import.srt 7.7 kB
11. Milestone Project 1 Supervised Learning (Classification)/18. Evaluating Our Model 2.srt 7.6 kB
18. Learn Python Part 2/15. While Loops.srt 7.5 kB
17. Learn Python/44. Dictionary Methods 2.srt 7.3 kB
9. Scikit-learn Creating Machine Learning Models/35. Machine Learning Model Evaluation.html 7.3 kB
17. Learn Python/40. Dictionaries.srt 7.3 kB
2. Machine Learning 101/4. How Did We Get Here.srt 7.2 kB
17. Learn Python/1. What Is A Programming Language.srt 7.2 kB
18. Learn Python Part 2/11. Iterables.srt 7.0 kB
3. Machine Learning and Data Science Framework/7. Features In Data.srt 6.9 kB
18. Learn Python Part 2/33. global Keyword.srt 6.8 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/2. Project Overview.srt 6.8 kB
3. Machine Learning and Data Science Framework/3. 6 Step Machine Learning Framework.srt 6.8 kB
18. Learn Python Part 2/42. Set Comprehensions.srt 6.7 kB
3. Machine Learning and Data Science Framework/5. Types of Data.srt 6.7 kB
17. Learn Python/3. How To Run Python Code.srt 6.6 kB
9. Scikit-learn Creating Machine Learning Models/10. Quick Tip Clean, Transform, Reduce.srt 6.6 kB
18. Learn Python Part 2/16. While Loops 2.srt 6.6 kB
8. Matplotlib Plotting and Data Visualization/7. Subplots Option 2.srt 6.5 kB
14. Neural Networks Deep Learning/7. Setting Up Our Data.srt 6.5 kB
2. Machine Learning 101/2. AIMachine LearningData Science.srt 6.5 kB
9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.srt 6.5 kB
13. Data Engineering/4. What Is A Data Engineer 2.srt 6.5 kB
14. Neural Networks Deep Learning/5. Google Colab Workspace.srt 6.5 kB
17. Learn Python/19. Strings.srt 6.4 kB
18. Learn Python Part 2/37. map().srt 6.4 kB
3. Machine Learning and Data Science Framework/9. Modelling - Picking the Model.srt 6.4 kB
5. Data Science Environment Setup/4. Conda Environments.srt 6.3 kB
2. Machine Learning 101/8. What Is Machine Learning Round 2.srt 6.2 kB
3. Machine Learning and Data Science Framework/13. Tools We Will Use.srt 6.1 kB
14. Neural Networks Deep Learning/12. Optional GPU and Google Colab.srt 6.1 kB
18. Learn Python Part 2/4. Truthy vs Falsey.srt 6.1 kB
18. Learn Python Part 2/23. Default Parameters and Keyword Arguments.srt 6.1 kB
14. Neural Networks Deep Learning/29. Summarizing Our Model.srt 6.1 kB
9. Scikit-learn Creating Machine Learning Models/26. Evaluating A Classification Model 1 (Accuracy).srt 6.0 kB
18. Learn Python Part 2/13. range().srt 6.0 kB
8. Matplotlib Plotting and Data Visualization/19. Saving And Sharing Your Plots.srt 6.0 kB
17. Learn Python/37. Common List Patterns.srt 6.0 kB
9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Regression Model 2 (MAE).srt 5.8 kB
17. Learn Python/45. Tuples.srt 5.8 kB
2. Machine Learning 101/5. Exercise YouTube Recommendation Engine.srt 5.8 kB
17. Learn Python/31. Lists.srt 5.7 kB
14. Neural Networks Deep Learning/31. Preventing Overfitting.srt 5.7 kB
15. Storytelling + Communication How To Present Your Work/4. Communicating With Co-Workers.srt 5.7 kB
17. Learn Python/11. Math Functions.srt 5.6 kB
13. Data Engineering/5. What Is A Data Engineer 3.srt 5.5 kB
18. Learn Python Part 2/28. Clean Code.srt 5.5 kB
17. Learn Python/29. DEVELOPER FUNDAMENTALS II.srt 5.4 kB
18. Learn Python Part 2/3. Indentation In Python.srt 5.4 kB
2. Machine Learning 101/6. Types of Machine Learning.srt 5.4 kB
1. Introduction/4. Your First Day.srt 5.4 kB
17. Learn Python/43. Dictionary Methods.srt 5.4 kB
7. NumPy/14. Comparison Operators.srt 5.4 kB
18. Learn Python Part 2/17. break, continue, pass.srt 5.4 kB
18. Learn Python Part 2/26. Methods vs Functions.srt 5.4 kB
17. Learn Python/12. DEVELOPER FUNDAMENTALS I.srt 5.3 kB
17. Learn Python/8. Python Data Types.srt 5.3 kB
18. Learn Python Part 2/38. filter().srt 5.2 kB
13. Data Engineering/13. Kafka and Stream Processing.srt 5.2 kB
17. Learn Python/36. List Methods 3.srt 5.1 kB
17. Learn Python/22. Escape Sequences.srt 5.1 kB
3. Machine Learning and Data Science Framework/12. Experimentation.srt 5.1 kB
18. Learn Python Part 2/43. Exercise Comprehensions.srt 5.1 kB
13. Data Engineering/3. What Is A Data Engineer.srt 5.0 kB
18. Learn Python Part 2/22. Parameters and Arguments.srt 5.0 kB
3. Machine Learning and Data Science Framework/10. Modelling - Tuning.srt 5.0 kB
15. Storytelling + Communication How To Present Your Work/2. Communicating Your Work.srt 5.0 kB
18. Learn Python Part 2/5. Ternary Operator.srt 4.9 kB
17. Learn Python/15. Optional bin() and complex.srt 4.9 kB
18. Learn Python Part 2/35. Why Do We Need Scope.srt 4.9 kB
4. The 2 Paths/1. The 2 Paths.srt 4.8 kB
13. Data Engineering/11. Hadoop, HDFS and MapReduce.srt 4.8 kB
18. Learn Python Part 2/30. Exercise Functions.srt 4.8 kB
3. Machine Learning and Data Science Framework/1. Section Overview.srt 4.8 kB
18. Learn Python Part 2/14. enumerate().srt 4.7 kB
15. Storytelling + Communication How To Present Your Work/3. Communicating With Managers.srt 4.6 kB
15. Storytelling + Communication How To Present Your Work/6. Communicating With Outside World.srt 4.6 kB
17. Learn Python/35. List Methods 2.srt 4.6 kB
14. Neural Networks Deep Learning/10. Optional TensorFlow 2.0 Default Issue.srt 4.6 kB
18. Learn Python Part 2/6. Short Circuiting.srt 4.6 kB
18. Learn Python Part 2/20. Exercise Find Duplicates.srt 4.5 kB
5. Data Science Environment Setup/2. Introducing Our Tools.srt 4.4 kB
3. Machine Learning and Data Science Framework/6. Types of Evaluation.srt 4.4 kB
18. Learn Python Part 2/27. Docstrings.srt 4.4 kB
13. Data Engineering/1. Data Engineering Introduction.srt 4.4 kB
17. Learn Python/42. Dictionary Keys.srt 4.3 kB
17. Learn Python/33. Matrix.srt 4.2 kB
9. Scikit-learn Creating Machine Learning Models/1. Section Overview.srt 4.2 kB
15. Storytelling + Communication How To Present Your Work/7. Storytelling.srt 4.2 kB
18. Learn Python Part 2/34. nonlocal Keyword.srt 4.2 kB
17. Learn Python/27. Booleans.srt 4.0 kB
14. Neural Networks Deep Learning/44. Finishing Dog Vision Where to next.html 4.0 kB
13. Data Engineering/6. What Is A Data Engineer 4.srt 4.0 kB
18. Learn Python Part 2/31. Scope.srt 3.9 kB
6. Pandas Data Analysis/1. Section Overview.srt 3.8 kB
3. Machine Learning and Data Science Framework/2. Introducing Our Framework.srt 3.8 kB
20. Where To Go From Here/2. Thank You.srt 3.7 kB
17. Learn Python/41. DEVELOPER FUNDAMENTALS III.srt 3.7 kB
18. Learn Python Part 2/12. Exercise Tricky Counter.srt 3.7 kB
17. Learn Python/13. Operator Precedence.srt 3.6 kB
17. Learn Python/25. Immutability.srt 3.6 kB
5. Data Science Environment Setup/3. What is Conda.srt 3.5 kB
15. Storytelling + Communication How To Present Your Work/1. Section Overview.srt 3.4 kB
18. Learn Python Part 2/39. zip().srt 3.3 kB
15. Storytelling + Communication How To Present Your Work/8. Communicating and sharing your work Further reading.html 3.2 kB
11. Milestone Project 1 Supervised Learning (Classification)/1. Section Overview.srt 3.2 kB
7. NumPy/1. Section Overview.srt 3.2 kB
9. Scikit-learn Creating Machine Learning Models/42. Quick Tip Correlation Analysis.srt 3.2 kB
17. Learn Python/21. Type Conversion.srt 3.2 kB
17. Learn Python/46. Tuples 2.srt 3.1 kB
18. Learn Python Part 2/1. Breaking The Flow.srt 3.1 kB
16. Career Advice + Extra Bits/7. JTS Start With Why.srt 3.0 kB
17. Learn Python/18. Augmented Assignment Operator.srt 3.0 kB
17. Learn Python/38. List Unpacking.srt 3.0 kB
17. Learn Python/6. Exercise How Does Python Work.srt 2.9 kB
14. Neural Networks Deep Learning/1. Section Overview.srt 2.8 kB
14. Neural Networks Deep Learning/24. Optional How machines learn and what's going on behind the scenes.html 2.8 kB
8. Matplotlib Plotting and Data Visualization/1. Section Overview.srt 2.8 kB
17. Learn Python/7. Learning Python.srt 2.6 kB
1. Introduction/3. Exercise Meet The Community.html 2.6 kB
16. Career Advice + Extra Bits/6. JTS Learn to Learn.srt 2.6 kB
5. Data Science Environment Setup/10. Sharing your Conda Environment.html 2.5 kB
2. Machine Learning 101/9. Section Review.srt 2.4 kB
8. Matplotlib Plotting and Data Visualization/8. Quick Tip Data Visualizations.srt 2.4 kB
13. Data Engineering/12. Apache Spark and Apache Flink.srt 2.4 kB
17. Learn Python/39. None.srt 2.2 kB
14. Neural Networks Deep Learning/8. Setting Up Our Data 2.srt 2.2 kB
1. Introduction/2. Join Our Online Classroom!.html 2.2 kB
7. NumPy/17. Assignment NumPy Practice.html 2.2 kB
5. Data Science Environment Setup/1. Section Overview.srt 2.2 kB
9. Scikit-learn Creating Machine Learning Models/47. Scikit-Learn Practice.html 2.1 kB
8. Matplotlib Plotting and Data Visualization/20. Assignment Matplotlib Practice.html 2.1 kB
6. Pandas Data Analysis/12. Assignment Pandas Practice.html 2.1 kB
9. Scikit-learn Creating Machine Learning Models/13. Note Correction in the upcoming video.html 2.1 kB
9. Scikit-learn Creating Machine Learning Models/18. Quick Tip How ML Algorithms Work.srt 2.0 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/1. Section Overview.srt 1.9 kB
20. Where To Go From Here/1. Become An Alumni.html 1.8 kB
17. Learn Python/17. Expressions vs Statements.srt 1.8 kB
21. Extras/1. Bonus Special Thank You Gift!.html 1.6 kB
16. Career Advice + Extra Bits/14. Exercise Contribute To Open Source.html 1.5 kB
17. Learn Python/20. String Concatenation.srt 1.5 kB
7. NumPy/3. Quick Note Correction In Next Video.html 1.3 kB
18. Learn Python Part 2/44. Python Exam Testing Your Understanding.html 1.1 kB
6. Pandas Data Analysis/5. Data from URLs.html 1.1 kB
5. Data Science Environment Setup/9. Linux Environment Setup.html 1.1 kB
7. NumPy/18. Optional Extra NumPy resources.html 1.0 kB
Verify Files.txt 1.0 kB
9. Scikit-learn Creating Machine Learning Models/5. Quick Note Upcoming Videos.html 1.0 kB
3. Machine Learning and Data Science Framework/14. Optional Elements of AI.html 975 Bytes
6. Pandas Data Analysis/2. Downloading Workbooks and Assignments.html 967 Bytes
18. Learn Python Part 2/50. Next Steps.html 959 Bytes
16. Career Advice + Extra Bits/13. Coding Challenges.html 948 Bytes
10. Supervised Learning Classification + Regression/1. Milestone Projects!.html 738 Bytes
4. The 2 Paths/2. Python + Machine Learning Monthly.html 734 Bytes
19. Bonus Learn Advanced Statistics and Mathematics for FREE!/1. Statistics and Mathematics.html 710 Bytes
16. Career Advice + Extra Bits/1. Endorsements On LinkedIn.html 688 Bytes
17. Learn Python/14. Exercise Operator Precedence.html 683 Bytes
8. Matplotlib Plotting and Data Visualization/10. Quick Note Regular Expressions.html 632 Bytes
16. Career Advice + Extra Bits/2. Quick Note Upcoming Video.html 587 Bytes
14. Neural Networks Deep Learning/3. Setting Up With Google.html 568 Bytes
16. Career Advice + Extra Bits/5. Quick Note Upcoming Videos.html 565 Bytes
13. Data Engineering/8. Quick Note Upcoming Video.html 481 Bytes
18. Learn Python Part 2/46. Quick Note Upcoming Videos.html 448 Bytes
13. Data Engineering/10. Optional Learn SQL.html 410 Bytes
18. Learn Python Part 2/25. Exercise Tesla.html 402 Bytes
9. Scikit-learn Creating Machine Learning Models/3. Quick Note Upcoming Video.html 390 Bytes
6. Pandas Data Analysis/7.1 car-sales.csv 369 Bytes
16. Career Advice + Extra Bits/8. Quick Note Upcoming Videos.html 352 Bytes
16. Career Advice + Extra Bits/4. Learning Guideline.html 310 Bytes
6. Pandas Data Analysis/9.2 car-sales-missing-data.csv 287 Bytes
17. Learn Python/9. How To Succeed.html 280 Bytes
9. Scikit-learn Creating Machine Learning Models/17. Quick Note Decision Trees.html 221 Bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/19.1 End-to-end Bluebook Bulldozer Regression Notebook (same as in videos).html 214 Bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/2.2 End-to-end Bluebook Bulldozer Regression Notebook (same as in videos).html 214 Bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/19.2 End-to-end Bluebook Bulldozer Regression Notebook (with annotations).html 208 Bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/2.3 End-to-end Bluebook Bulldozer Regression Notebook (with annotations).html 208 Bytes
11. Milestone Project 1 Supervised Learning (Classification)/2.3 End-to-end Heart Disease Classification Notebook (same as in videos).html 207 Bytes
11. Milestone Project 1 Supervised Learning (Classification)/21.1 End-to-end Heart Disease Classification Notebook (same as in videos).html 207 Bytes
11. Milestone Project 1 Supervised Learning (Classification)/2.2 End-to-end Heart Disease Classification Notebook (with annotations).html 201 Bytes
11. Milestone Project 1 Supervised Learning (Classification)/21.2 End-to-end Heart Disease Classification Notebook (with annotations).html 201 Bytes
9. Scikit-learn Creating Machine Learning Models/2.1 Introduction to Scikit-Learn Jupyter Notebook (from the upcoming videos).html 197 Bytes
9. Scikit-learn Creating Machine Learning Models/46.1 Introduction to Scikit-Learn Jupyter Notebook (from the videos).html 197 Bytes
8. Matplotlib Plotting and Data Visualization/19.1 Introduction to Matplotlib Notebook (from the videos).html 195 Bytes
8. Matplotlib Plotting and Data Visualization/2.1 Introduction to Matplotlib Jupyter Notebook (from the upcoming videos).html 195 Bytes
9. Scikit-learn Creating Machine Learning Models/6.1 Scikit-Learn Reference Notebook.html 194 Bytes
9. Scikit-learn Creating Machine Learning Models/7.1 Example Scikit-Learn Workflow Notebook.html 192 Bytes
14. Neural Networks Deep Learning/43.1 End-to-end Dog Vision Notebook (from the videos).html 191 Bytes
6. Pandas Data Analysis/11.1 Introduction to Pandas Jupyter Notebook (from the videos).html 191 Bytes
6. Pandas Data Analysis/3.4 Introduction to Pandas Jupyter Notebook (from the upcoming videos).html 191 Bytes
9. Scikit-learn Creating Machine Learning Models/2.3 Introduction to Scikit-Learn Jupyter Notebook (with annotations).html 191 Bytes
9. Scikit-learn Creating Machine Learning Models/46.2 Introduction to Scikit-Learn Jupyter Notebook (with annotations).html 191 Bytes
7. NumPy/16.2 Introduction to NumPy Jupyter Notebook (from the videos).html 190 Bytes
7. NumPy/2.2 Introduction to NumPy Jupyter Notebook (from the upcoming videos).html 190 Bytes
14. Neural Networks Deep Learning/43.2 End-to-end Dog Vision Notebook (with annotations).html 185 Bytes
6. Pandas Data Analysis/11.2 Introduction to Pandas Jupyter Notebook (with annotations).html 185 Bytes
6. Pandas Data Analysis/3.2 Introduction to Pandas Jupyter Notebook (with annotations).html 185 Bytes
7. NumPy/16.3 Introduction to NumPy Jupyter Notebook (with annotations).html 184 Bytes
7. NumPy/2.1 Introduction to NumPy Jupyter Notebook (with annotations).html 184 Bytes
14. Neural Networks Deep Learning/4.3 End-to-end Dog Vision Notebook (the project we'll be working through).html 182 Bytes
14. Neural Networks Deep Learning/42.1 Dog Vision Predictions with MobileNetV2 Ready for Kaggle Submission.html 180 Bytes
14. Neural Networks Deep Learning/27.2 Step by step breakdown of a convolutional neural network (what MobileNetV2 is made of).html 172 Bytes
5. Data Science Environment Setup/10.1 Conda documentation on sharing an environment.html 172 Bytes
14. Neural Networks Deep Learning/41.1 Dog Vision Prediction Probabilities Array.html 170 Bytes
18. Learn Python Part 2/4.1 Truthy vs Falsey Stackoverflow.html 170 Bytes
14. Neural Networks Deep Learning/28.1 [Article] How to choose loss & activation functions when building a deep learning model.html 169 Bytes
5. Data Science Environment Setup/3.1 Getting your computer ready for machine learning How.html 167 Bytes
14. Neural Networks Deep Learning/27.3 MobileNetV2 (the model we're using) architecture explanation by Sik-Ho Tsang.html 163 Bytes
17. Learn Python/5.1 Python 2 vs Python 3.html 161 Bytes
2. Machine Learning 101/7. Are You Getting It Yet.html 160 Bytes
11. Milestone Project 1 Supervised Learning (Classification)/2.1 Structured Data Projects on GitHub.html 155 Bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/2.4 Structured Data Projects on GitHub.html 155 Bytes
3. Machine Learning and Data Science Framework/3.1 A 6 Step Field Guide for Machine Learning Modelling (blog post).html 147 Bytes
6. Pandas Data Analysis/9.1 Jake VanderPlas's Data Manipulation with Pandas.html 146 Bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/9.1 Pandas Categorical Datatype Documentation.html 143 Bytes
15. Storytelling + Communication How To Present Your Work/2.1 How to Think About Communicating and Sharing Your Work (blog post).html 142 Bytes
5. Data Science Environment Setup/3.3 Getting started with Conda (documentation).html 139 Bytes
14. Neural Networks Deep Learning/31.1 Early Stopping Callback (a way to stop your model from training when it stops improving) Documentation.html 136 Bytes
14. Neural Networks Deep Learning/30.1 TensorBoard Callback Documentation.html 134 Bytes
9. Scikit-learn Creating Machine Learning Models/15.1 Scikit-Learn machine learning map (how to choose the right machine learning model).html 133 Bytes
14. Neural Networks Deep Learning/25.2 MobileNetV2 (the model we're using) on TensorFlow Hub.html 132 Bytes
6. Pandas Data Analysis/3.3 10-minutes to pandas (from the pandas documentation).html 132 Bytes
14. Neural Networks Deep Learning/10.1 Loading TensorFlow 2.0 into a Colab Notebook (if it isn't the default).html 129 Bytes
14. Neural Networks Deep Learning/14.1 Documentation on how many images Google recommends for image problems.html 129 Bytes
14. Neural Networks Deep Learning/35.1 TensorFlow documentation for the unbatch() function.html 127 Bytes
13. Data Engineering/7.2 OLTP vs OLAP.html 126 Bytes
14. Neural Networks Deep Learning/4.1 Kaggle Dog Breed Identification Competition (the basis of our upcoming project).html 119 Bytes
17. Learn Python/43.1 Dictionary Methods.html 119 Bytes
7. NumPy/12.1 Matrix Multiplication Explained.html 119 Bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/2.1 Kaggle Bluebook for Bulldozers Competition.html 118 Bytes
14. Neural Networks Deep Learning/21.1 Yann LeCun's (OG of deep learning) Tweet on Batch Sizes.html 118 Bytes
13. Data Engineering/7.1 A Primer on ACID Transactions.html 117 Bytes
17. Learn Python/16.1 Python Keywords.html 117 Bytes
17. Learn Python/35.1 Python Keywords.html 117 Bytes
5. Data Science Environment Setup/11.4 Dataquest Jupyter Notebook for Beginners Tutorial.html 117 Bytes
14. Neural Networks Deep Learning/12.2 Introduction to Google Colab example notebook.html 116 Bytes
14. Neural Networks Deep Learning/4.4 Introduction to Google Colab example notebook.html 116 Bytes
17. Learn Python/18.1 Exercise Repl.html 116 Bytes
7. NumPy/10.1 Standard deviation and variance explained.html 116 Bytes
7. NumPy/8.1 Standard deviation and variance explained.html 116 Bytes
7. NumPy/9.1 Standard deviation and variance explained.html 116 Bytes
14. Neural Networks Deep Learning/6.1 Kaggle Dog Breed Identification Competition Data.html 115 Bytes
17. Learn Python/26.2 String Methods.html 115 Bytes
14. Neural Networks Deep Learning/11.1 Google Colab example GPU usage.html 114 Bytes
14. Neural Networks Deep Learning/12.1 Google Colab Example of GPU speed up versus CPU.html 114 Bytes
14. Neural Networks Deep Learning/18.2 Documentation for loading images in TensorFlow.html 114 Bytes
17. Learn Python/46.1 Tuple Methods.html 114 Bytes
14. Neural Networks Deep Learning/4.5 Google Colab IO example (how to get data in and out of your Colab notebook).html 113 Bytes
14. Neural Networks Deep Learning/6.2 Google Colab IO example (how to get data in and out of your Colab notebook).html 113 Bytes
17. Learn Python/34.1 List Methods.html 113 Bytes
17. Learn Python/48.1 Sets Methods.html 112 Bytes
17. Learn Python/15.1 Base Numbers.html 111 Bytes
5. Data Science Environment Setup/11.2 Jupyter Notebook documentation.html 111 Bytes
14. Neural Networks Deep Learning/5.2 Google Colab FAQ (things you should know about Google Colab).html 110 Bytes
17. Learn Python/26.1 Built in Functions.html 109 Bytes
14. Neural Networks Deep Learning/17.1 Blog post by Rachel Thomas (of fast.ai) on how and why you should create a validation set.html 108 Bytes
14. Neural Networks Deep Learning/26.1 Keras in TensorFlow Overview Documentation.html 108 Bytes
18. Learn Python Part 2/30.1 Solution Repl.html 108 Bytes
6. Pandas Data Analysis/13.1 Course notebooks - Github.html 108 Bytes
9. Scikit-learn Creating Machine Learning Models/2.2 Scikit-Learn Documentation.html 108 Bytes
14. Neural Networks Deep Learning/27.1 The Softmax Function (activation function we use in our model).html 107 Bytes
5. Data Science Environment Setup/5.1 Miniconda download documentation.html 107 Bytes
5. Data Science Environment Setup/7.1 Miniconda download documentation.html 107 Bytes
15. Storytelling + Communication How To Present Your Work/6.1 fast_template by fast.ai (a template you can use for your blog on GitHub Pages).html 106 Bytes
17. Learn Python/13.1 Exercise Repl.html 106 Bytes
17. Learn Python/14.1 Exercise Repl.html 106 Bytes
17. Learn Python/29.1 Python Comments Best Practices.html 106 Bytes
6. Pandas Data Analysis/3.1 Pandas Documentation.html 106 Bytes
17. Learn Python/10.1 Floating point numbers.html 104 Bytes
17. Learn Python/23.1 Exercise Repl.html 104 Bytes
17. Learn Python/5.2 The Story of Python.html 104 Bytes
8. Matplotlib Plotting and Data Visualization/2.2 Matplotlib Documentation.html 103 Bytes
18. Learn Python Part 2/20.1 Solution Repl.html 102 Bytes
18. Learn Python Part 2/43.1 Solution Repl.html 102 Bytes
17. Learn Python/24.1 Exercise Repl.html 101 Bytes
2. Machine Learning 101/3.1 Teachable Machine.html 101 Bytes
18. Learn Python Part 2/43.2 Exercise Repl.html 100 Bytes
18. Learn Python Part 2/18.1 Solution Repl.html 99 Bytes
18. Learn Python Part 2/18.2 Exercise Repl.html 99 Bytes
14. Neural Networks Deep Learning/18.1 TensorFlow guidelines for loading all kinds of data (turning your data into Tensors).html 98 Bytes
17. Learn Python/44.1 Exercise Repl.html 97 Bytes
14. Neural Networks Deep Learning/25.3 Andrei Karpathy's talk on AI at Tesla.html 95 Bytes
14. Neural Networks Deep Learning/4.2 Google Colab (our workspace for the upcoming project).html 95 Bytes
14. Neural Networks Deep Learning/5.1 Google Colab (our workspace for the upcoming project).html 95 Bytes
18. Learn Python Part 2/34.1 Solution Repl.html 95 Bytes
6. Pandas Data Analysis/13.2 Google Colab.html 95 Bytes
17. Learn Python/35.2 Exercise Repl.html 94 Bytes
17. Learn Python/37.1 Exercise Repl.html 94 Bytes
17. Learn Python/33.1 Exercise Repl.html 93 Bytes
5. Data Science Environment Setup/3.4 Conda documentation.html 93 Bytes
13. Data Engineering/2.1 Kaggle.html 92 Bytes
17. Learn Python/32.1 Exercise Repl.html 92 Bytes
18. Learn Python Part 2/12.1 Solution Repl.html 92 Bytes
17. Learn Python/48.2 Exercise Repl.html 91 Bytes
15. Storytelling + Communication How To Present Your Work/6.2 Devblog by Hashnode (an easy and free way to create a blog you own).html 89 Bytes
14. Neural Networks Deep Learning/25.4 Papers with Code (a great resource for some of the best machine learning papers with code examples).html 88 Bytes
2. Machine Learning 101/5.1 Machine Learning Playground.html 88 Bytes
14. Neural Networks Deep Learning/25.5 PyTorch Hub (PyTorch version of TensorFlow Hub).html 85 Bytes
7. NumPy/2.3 NumPy Documentation.html 83 Bytes
14. Neural Networks Deep Learning/23.1 TensorFlow Hub (resource for pre-trained deep learning models and more).html 79 Bytes
14. Neural Networks Deep Learning/25.1 TensorFlow Hub (resource for pre-trained deep learning models and more).html 79 Bytes
[FreeAllCourse.Com].url 52 Bytes

==查看完整文档列表==

上一个：Kingdom Come - Deliverance Royal Edition v1.9.4.404-502 (34099) [GOG]80.5 GB

24小时热门磁力链接

Andor [HDTV 720p][Cap.205] 8145次下载 Cap HDTV 720p
Маня и Груня.2024.WEB-DL 720p.Files-x 5109次下载 2024 WEB DL
Havoc.2025.1080p.NF.WEB-DL.DDP5.1.Atmos.H.264-EniaHD.mkv 5077次下载 WEB DL DDP5
The.Super.Cube.S01E09.1080p.iQ.WEB-DL.AAC2.0.H.264-VARYG.mkv 5040次下载 WEB DL Cube
Star.Wars.Andor.S02E05.I.Have.Friends.Everywhere.1080p.DS... 4944次下载 WEB DL Star
新桥恋人.电影港地址发布页 www.dygang.me 收藏不迷路 4365次下载 me www 发布页
Night at the Museum Battle of the Smithsonian 2009 2160p... 4161次下载 KiNGDOM WEB DL
www.UIndex.org - ... 4126次下载 www MeGusta HEVC
Palma.2.2024.WEB-DL.1080p.ExKinoRay.mkv 4000次下载 WEB DL 2.2024
Guns N' Roses - Greatest Hits Live Broadcast Collection... 3915次下载 Live Remastered Hits

本周热门磁力链接

Andor [HDTV 720p][Cap.205] 8145次下载 Cap HDTV 720p
(同人CG集) [白色絵の具 (無味ムスミ)] 友達の母が巨乳で金髪の淫乱美女でした.zip 6346次下载 zip 巨乳 CG
You.S05E02.720p.HEVC.x265-MeGusta[EZTVx.to].mkv 6221次下载 S05E02 HEVC 720p
up-mod-minecraft-play-with-friends-v1-21-80-28-... 6023次下载 982108028 mod play
the.last.of.us.s02e02.1080p.web.h264-successful... 5335次下载 web last h264
异世降临.6v电影地址发布页 www.6v123.net 收藏不迷路 5220次下载 www 发布页 6v123
Opasnaya.blizost.S01.2025.WEB-DL.1080p 5127次下载 WEB DL S01
Маня и Груня.2024.WEB-DL 720p.Files-x 5109次下载 2024 WEB DL
Andor.S02E02.Sagrona.Teema.1080p.HEVC.x265-MeGu... 5100次下载 HEVC Andor mkv
Havoc.2025.1080p.NF.WEB-DL.DDP5.1.Atmos.H.264-E... 5077次下载 WEB DL DDP5

种子标签

种子评价

优质的种子 (0) 假种子 (0) 有密码 (0) 低质量 (0) 有病毒 (0) 无法下载 (0)
欢迎对种子质量进行评价。

人气女优

北川ゆい Akira COCOLO Saiko あいだももあさのくるみあまいれもんいしかわ愛里いとうしいなうさみ恭香うちだまひろかぐやひめかとりこのみかないかほくすのき琴美クミコグレースくらもとまい（葉月ありさ）さとみ中村あみしいな純菜しのざきさとみ（三沢亜也）牧本千幸（つかもと友希）眞木ありさデヴィテラパトリックドミニカともさかまいともさか愛なごみもえひなこ

分享BT种子/磁力链接

亲，你知道吗？下载的人越多速度越快，赶快把本页面分享给好友一起下载吧^_^

磁力管家