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Complete Machine Learning Data Science Bootcamp 2021

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Complete Machine Learning Data Science Bootcamp 2021

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Files:

8. Windows Environment Setup 2.mp4 227.6 MB
READ_ME.txt 425 bytes
1. Course Outline.mp4 77.3 MB
1. Course Outline.srt 9.2 KB
2. Join Our Online Classroom!.html 2.5 KB
3. Exercise Meet The Community.html 2.5 KB
4. Your First Day.mp4 27.9 MB
4. Your First Day.srt 5.3 KB
READ_ME.txt 425 bytes
1. What Is Machine Learning.mp4 28.3 MB
1. What Is Machine Learning.srt 8.7 KB
2. AIMachine LearningData Science.mp4 19.7 MB
2. AIMachine LearningData Science.srt 6.4 KB
3. Exercise Machine Learning Playground.mp4 42.6 MB
3. Exercise Machine Learning Playground.srt 8.1 KB
3.1 Teachable Machine.html 101 bytes
4. How Did We Get Here.mp4 30.5 MB
4. How Did We Get Here.srt 7.1 KB
5. Exercise YouTube Recommendation Engine.mp4 19.4 MB
5. Exercise YouTube Recommendation Engine.srt 5.7 KB
5.1 Machine Learning Playground.html 88 bytes
6. Types of Machine Learning.mp4 22.8 MB
6. Types of Machine Learning.srt 5.3 KB
7. Are You Getting It Yet.html 160 bytes
8. What Is Machine Learning Round 2.mp4 25.5 MB
8. What Is Machine Learning Round 2.srt 6.1 KB
9. Section Review.mp4 5.6 MB
9. Section Review.srt 2.3 KB
1. Section Overview.mp4 13.3 MB
1. Section Overview.srt 4.7 KB
2. Introducing Our Framework.mp4 11.4 MB
2. Introducing Our Framework.srt 3.7 KB
3. 6 Step Machine Learning Framework.mp4 23.5 MB
3. 6 Step Machine Learning Framework.srt 6.6 KB
3.1 A 6 Step Field Guide for Machine Learning Modelling (blog post).html 147 bytes
4. Types of Machine Learning Problems.mp4 60.5 MB
4. Types of Machine Learning Problems.srt 14.0 KB
5. Types of Data.mp4 29.3 MB
5. Types of Data.srt 6.5 KB
6. Types of Evaluation.mp4 17.8 MB
6. Types of Evaluation.srt 4.3 KB
7. Features In Data.mp4 36.8 MB
7. Features In Data.srt 6.8 KB
8. Modelling - Splitting Data.mp4 27.5 MB
8. Modelling - Splitting Data.srt 7.7 KB
9. Modelling - Picking the Model.mp4 23.2 MB
9. Modelling - Picking the Model.srt 6.2 KB
10. Modelling - Tuning.mp4 16.0 MB
10. Modelling - Tuning.srt 4.9 KB
11. Modelling - Comparison.mp4 44.9 MB
11. Modelling - Comparison.srt 13.1 KB
12. Overfitting and Underfitting Definitions.html 2.0 KB
13. Experimentation.mp4 21.3 MB
13. Experimentation.srt 5.0 KB
14. Tools We Will Use.mp4 27.3 MB
14. Tools We Will Use.srt 6.0 KB
15. Optional Elements of AI.html 975 bytes
1. The 2 Paths.mp4 9.7 MB
1. The 2 Paths.srt 4.7 KB
2. Python + Machine Learning Monthly.html 917 bytes
3. Endorsements On LinkedIN.html 2.1 KB
1. Section Overview.mp4 6.0 MB
1. Section Overview.srt 2.1 KB
2. Introducing Our Tools.mp4 19.3 MB
2. Introducing Our Tools.srt 4.3 KB
3. What is Conda.mp4 12.5 MB
3. What is Conda.srt 3.4 KB
3.1 Getting started with Conda (documentation).html 139 bytes
3.2 conda-cheatsheet.pdf 211.3 KB
3.3 Getting your computer ready for machine learning How, what and why you should use Anaconda, Miniconda and Conda (blog post).html 167 bytes
3.4 Conda documentation.html 93 bytes
4. Conda Environments.mp4 30.6 MB
4. Conda Environments.srt 6.1 KB
5. Mac Environment Setup.mp4 144.4 MB
5. Mac Environment Setup.srt 23.9 KB
5.1 Miniconda download documentation.html 107 bytes
6. Mac Environment Setup 2.mp4 125.5 MB
6. Mac Environment Setup 2.srt 20.7 KB
7. Windows Environment Setup.mp4 47.9 MB
7. Windows Environment Setup.srt 7.6 KB
7.1 Miniconda download documentation.html 107 bytes
READ_ME.txt 425 bytes
8. Windows Environment Setup 2.srt 31.6 KB
9. Linux Environment Setup.html 1.0 KB
10. Sharing your Conda Environment.html 2.4 KB
10.1 Conda documentation on sharing an environment.html 172 bytes
11. Jupyter Notebook Walkthrough.mp4 67.3 MB
11. Jupyter Notebook Walkthrough.srt 15.1 KB
11.1 6-step-ml-framework.png 324.2 KB
11.2 heart-disease.csv 11.1 KB
11.3 Dataquest Jupyter Notebook for Beginners Tutorial.html 117 bytes
11.4 Jupyter Notebook documentation.html 111 bytes
12. Jupyter Notebook Walkthrough 2.mp4 103.9 MB
12. Jupyter Notebook Walkthrough 2.srt 22.5 KB
13. Jupyter Notebook Walkthrough 3.mp4 71.4 MB
13. Jupyter Notebook Walkthrough 3.srt 11.5 KB
1. Section Overview.mp4 10.9 MB
1. Section Overview.srt 3.7 KB
2. Downloading Workbooks and Assignments.html 967 bytes
3. Pandas Introduction.mp4 27.4 MB
3. Pandas Introduction.srt 7.0 KB
3.1 Introduction to Pandas Jupyter Notebook (from the upcoming videos).html 191 bytes
3.2 10-minutes to pandas (from the pandas documentation).html 127 bytes
3.3 Pandas Documentation.html 106 bytes
3.4 Introduction to Pandas Jupyter Notebook (with annotations).html 185 bytes
4. Series, Data Frames and CSVs.mp4 95.4 MB
4. Series, Data Frames and CSVs.srt 16.8 KB
4.1 pandas-anatomy-of-a-dataframe.png 333.2 KB
5. Data from URLs.html 1.1 KB
6. Describing Data with Pandas.mp4 75.6 MB
6. Describing Data with Pandas.srt 13.6 KB
7. Selecting and Viewing Data with Pandas.mp4 72.3 MB
7. Selecting and Viewing Data with Pandas.srt 14.6 KB
7.1 car-sales.csv 369 bytes
8. Selecting and Viewing Data with Pandas Part 2.mp4 106.5 MB
8. Selecting and Viewing Data with Pandas Part 2.srt 17.9 KB
9. Manipulating Data.mp4 105.0 MB
9. Manipulating Data.srt 18.1 KB
9.1 Jake VanderPlas's Data Manipulation with Pandas.html 146 bytes
9.2 car-sales-missing-data.csv 287 bytes
10. Manipulating Data 2.mp4 86.5 MB
10. Manipulating Data 2.srt 13.8 KB
10.1 pandas-anatomy-of-a-dataframe.png 333.2 KB
11. Manipulating Data 3.mp4 91.0 MB
11. Manipulating Data 3.srt 13.7 KB
11.1 Introduction to Pandas Jupyter Notebook (with annotations).html 185 bytes
11.2 Introduction to Pandas Jupyter Notebook (from the videos).html 191 bytes
12. Assignment Pandas Practice.html 2.1 KB
13. How To Download The Course Assignments.mp4 66.8 MB
13. How To Download The Course Assignments.srt 11.1 KB
13.1 Google Colab.html 95 bytes
13.2 Course notebooks - Github.html 108 bytes
1. Section Overview.mp4 13.3 MB
1. Section Overview.srt 3.1 KB
2. NumPy Introduction.mp4 26.8 MB
2. NumPy Introduction.srt 7.5 KB
2.1 Introduction to NumPy Jupyter Notebook (with annotations).html 184 bytes
2.2 NumPy Documentation.html 83 bytes
2.3 Introduction to NumPy Jupyter Notebook (from the upcoming videos).html 190 bytes
3. Quick Note Correction In Next Video.html 1.2 KB
4. NumPy DataTypes and Attributes.mp4 79.0 MB
4. NumPy DataTypes and Attributes.srt 19.2 KB
5. Creating NumPy Arrays.mp4 66.8 MB
5. Creating NumPy Arrays.srt 12.4 KB
6. NumPy Random Seed.mp4 51.9 MB
6. NumPy Random Seed.srt 9.7 KB
7. Viewing Arrays and Matrices.mp4 70.6 MB
7. Viewing Arrays and Matrices.srt 12.9 KB
8. Manipulating Arrays.mp4 80.7 MB
8. Manipulating Arrays.srt 16.2 KB
8.1 Standard deviation and variance explained.html 116 bytes
9. Manipulating Arrays 2.mp4 67.9 MB
9. Manipulating Arrays 2.srt 11.5 KB
9.1 Standard deviation and variance explained.html 116 bytes
10. Standard Deviation and Variance.mp4 51.2 MB
10. Standard Deviation and Variance.srt 9.3 KB
10.1 Standard deviation and variance explained.html 116 bytes
11. Reshape and Transpose.mp4 53.5 MB
11. Reshape and Transpose.srt 9.5 KB
12. Dot Product vs Element Wise.mp4 83.9 MB
12. Dot Product vs Element Wise.srt 15.3 KB
12.1 Matrix Multiplication Explained.html 119 bytes
13. Exercise Nut Butter Store Sales.mp4 91.3 MB
13. Exercise Nut Butter Store Sales.srt 17.0 KB
14. Comparison Operators.mp4 26.4 MB
14. Comparison Operators.srt 5.3 KB
15. Sorting Arrays.mp4 32.8 MB
15. Sorting Arrays.srt 8.8 KB
16. Turn Images Into NumPy Arrays.mp4 85.9 MB
16. Turn Images Into NumPy Arrays.srt 10.4 KB
16.1 Introduction to NumPy Jupyter Notebook (from the videos).html 190 bytes
16.2 Introduction to NumPy Jupyter Notebook (with annotations).html 184 bytes
16.3 numpy-images.zip 7.3 MB
17. Assignment NumPy Practice.html 2.2 KB
18. Optional Extra NumPy resources.html 1.0 KB
1. Section Overview.mp4 8.6 MB
1. Section Overview.srt 2.7 KB
2. Matplotlib Introduction.mp4 31.5 MB
2. Matplotlib Introduction.srt 8.0 KB
2.1 Introduction to Matplotlib Jupyter Notebook (from the upcoming videos).html 195 bytes
2.2 Matplotlib Documentation.html 103 bytes
3. Importing And Using Matplotlib.mp4 86.4 MB
3. Importing And Using Matplotlib.srt 16.0 KB
4. Anatomy Of A Matplotlib Figure.mp4 82.2 MB
4. Anatomy Of A Matplotlib Figure.srt 14.2 KB
4.1 matplotlib-anatomy-of-a-plot-with-code.png 654.8 KB
4.2 matplotlib-anatomy-of-a-plot.png 369.4 KB
5. Scatter Plot And Bar Plot.mp4 67.0 MB
5. Scatter Plot And Bar Plot.srt 14.7 KB
6. Histograms And Subplots.mp4 69.7 MB
6. Histograms And Subplots.srt 12.4 KB
7. Subplots Option 2.mp4 38.1 MB
7. Subplots Option 2.srt 6.4 KB
8. Quick Tip Data Visualizations.mp4 12.3 MB
8. Quick Tip Data Visualizations.srt 2.3 KB
9. Plotting From Pandas DataFrames.mp4 60.3 MB
9. Plotting From Pandas DataFrames.srt 9.0 KB
10. Quick Note Regular Expressions.html 632 bytes
11. Plotting From Pandas DataFrames 2.mp4 98.8 MB
11. Plotting From Pandas DataFrames 2.srt 13.6 KB
12. Plotting from Pandas DataFrames 3.mp4 74.7 MB
12. Plotting from Pandas DataFrames 3.srt 11.5 KB
13. Plotting from Pandas DataFrames 4.mp4 49.0 MB
13. Plotting from Pandas DataFrames 4.srt 9.4 KB
13.1 heart-disease.csv 11.1 KB
14. Plotting from Pandas DataFrames 5.mp4 57.0 MB
14. Plotting from Pandas DataFrames 5.srt 11.6 KB
15. Plotting from Pandas DataFrames 6.mp4 82.0 MB
15. Plotting from Pandas DataFrames 6.srt 11.1 KB
16. Plotting from Pandas DataFrames 7.mp4 119.8 MB
16. Plotting from Pandas DataFrames 7.srt 14.9 KB
17. Customizing Your Plots.mp4 92.2 MB
17. Customizing Your Plots.srt 14.0 KB
18. Customizing Your Plots 2.mp4 123.6 MB
18. Customizing Your Plots 2.srt 13.3 KB
19. Saving And Sharing Your Plots.mp4 49.5 MB
19. Saving And Sharing Your Plots.srt 5.8 KB
19.1 Introduction to Matplotlib Notebook (from the videos).html 195 bytes
20. Assignment Matplotlib Practice.html 2.1 KB
1. Section Overview.mp4 12.5 MB
1. Section Overview.srt 4.1 KB
2. Scikit-learn Introduction.mp4 40.6 MB
2. Scikit-learn Introduction.srt 10.6 KB
2.1 Introduction to Scikit-Learn Jupyter Notebook (from the upcoming videos).html 197 bytes
2.2 Scikit-Learn Documentation.html 108 bytes
2.3 Introduction to Scikit-Learn Jupyter Notebook (with annotations).html 191 bytes
3. Quick Note Upcoming Video.html 390 bytes
4. Refresher What Is Machine Learning.mp4 88.3 MB
4. Refresher What Is Machine Learning.srt 6.3 KB
5. Quick Note Upcoming Videos.html 1018 bytes
6. Scikit-learn Cheatsheet.mp4 75.1 MB
6. Scikit-learn Cheatsheet.srt 10.1 KB
6.1 Scikit-Learn Reference Notebook.html 194 bytes
7. Typical scikit-learn Workflow.mp4 190.2 MB
7. Typical scikit-learn Workflow.srt 31.7 KB
7.1 Example Scikit-Learn Workflow Notebook.html 192 bytes
8. Optional Debugging Warnings In Jupyter.mp4 176.1 MB
8. Optional Debugging Warnings In Jupyter.srt 25.5 KB
9. Getting Your Data Ready Splitting Your Data.mp4 63.7 MB
9. Getting Your Data Ready Splitting Your Data.srt 12.1 KB
9.1 scikit-learn-data.zip 20.8 KB
10. Quick Tip Clean, Transform, Reduce.mp4 16.5 MB
10. Quick Tip Clean, Transform, Reduce.srt 6.4 KB
11. Getting Your Data Ready Convert Data To Numbers.mp4 135.0 MB
11. Getting Your Data Ready Convert Data To Numbers.srt 22.7 KB
12. Getting Your Data Ready Handling Missing Values With Pandas.mp4 104.8 MB
12. Getting Your Data Ready Handling Missing Values With Pandas.srt 16.9 KB
13. Extension Feature Scaling.html 2.9 KB
14. Note Correction in the upcoming video (splitting data).html 2.2 KB
15. Getting Your Data Ready Handling Missing Values With Scikit-learn.mp4 136.9 MB
15. Getting Your Data Ready Handling Missing Values With Scikit-learn.srt 23.1 KB
16. Choosing The Right Model For Your Data.mp4 143.3 MB
16. Choosing The Right Model For Your Data.srt 21.4 KB
16.1 Scikit-Learn machine learning map (how to choose the right machine learning model).html 133 bytes
17. Choosing The Right Model For Your Data 2 (Regression).mp4 86.9 MB
17. Choosing The Right Model For Your Data 2 (Regression).srt 12.0 KB
18. Quick Note Decision Trees.html 221 bytes
19. Quick Tip How ML Algorithms Work.mp4 11.1 MB
19. Quick Tip How ML Algorithms Work.srt 1.9 KB
20. Choosing The Right Model For Your Data 3 (Classification).mp4 118.8 MB
20. Choosing The Right Model For Your Data 3 (Classification).srt 17.1 KB
21. Fitting A Model To The Data.mp4 56.6 MB
21. Fitting A Model To The Data.srt 9.3 KB
22. Making Predictions With Our Model.mp4 66.5 MB
22. Making Predictions With Our Model.srt 12.1 KB
23. predict() vs predict_proba().mp4 54.3 MB
23. predict() vs predict_proba().srt 11.6 KB
24. Making Predictions With Our Model (Regression).mp4 44.9 MB
24. Making Predictions With Our Model (Regression).srt 9.1 KB
25. Evaluating A Machine Learning Model (Score).mp4 87.1 MB
25. Evaluating A Machine Learning Model (Score).srt 12.9 KB
26. Evaluating A Machine Learning Model 2 (Cross Validation).mp4 96.0 MB
26. Evaluating A Machine Learning Model 2 (Cross Validation).srt 17.3 KB
27. Evaluating A Classification Model 1 (Accuracy).mp4 31.4 MB
27. Evaluating A Classification Model 1 (Accuracy).srt 5.9 KB
28. Evaluating A Classification Model 2 (ROC Curve).mp4 66.0 MB
28. Evaluating A Classification Model 2 (ROC Curve).srt 12.3 KB
29. Evaluating A Classification Model 3 (ROC Curve).mp4 50.6 MB
29. Evaluating A Classification Model 3 (ROC Curve).srt 10.0 KB
30. Reading Extension ROC Curve + AUC.html 1.5 KB
31. Evaluating A Classification Model 4 (Confusion Matrix).mp4 77.7 MB
31. Evaluating A Classification Model 4 (Confusion Matrix).srt 15.1 KB
31.1 Notebook from video with updated confusion matrix labels.html 191 bytes
32. Evaluating A Classification Model 5 (Confusion Matrix).mp4 63.8 MB
32. Evaluating A Classification Model 5 (Confusion Matrix).srt 11.2 KB
33. Evaluating A Classification Model 6 (Classification Report).mp4 87.2 MB
33. Evaluating A Classification Model 6 (Classification Report).srt 14.6 KB
34. Evaluating A Regression Model 1 (R2 Score).mp4 70.4 MB
34. Evaluating A Regression Model 1 (R2 Score).srt 12.0 KB
35. Evaluating A Regression Model 2 (MAE).mp4 28.5 MB
35. Evaluating A Regression Model 2 (MAE).srt 5.7 KB
36. Evaluating A Regression Model 3 (MSE).mp4 54.9 MB
36. Evaluating A Regression Model 3 (MSE).srt 9.2 KB
37. Machine Learning Model Evaluation.html 7.1 KB
38. Evaluating A Model With Cross Validation and Scoring Parameter.mp4 91.5 MB
38. Evaluating A Model With Cross Validation and Scoring Parameter.srt 18.0 KB
39. Evaluating A Model With Scikit-learn Functions.mp4 94.8 MB
39. Evaluating A Model With Scikit-learn Functions.srt 16.3 KB
40. Improving A Machine Learning Model.mp4 90.9 MB
40. Improving A Machine Learning Model.srt 14.9 KB
41. Tuning Hyperparameters.mp4 175.7 MB
41. Tuning Hyperparameters.srt 30.6 KB
42. Tuning Hyperparameters 2.mp4 116.8 MB
42. Tuning Hyperparameters 2.srt 17.0 KB
43. Tuning Hyperparameters 3.mp4 121.8 MB
43. Tuning Hyperparameters 3.srt 18.8 KB
44. Note Metric Comparison Improvement.html 2.2 KB
45. Quick Tip Correlation Analysis.mp4 16.9 MB
45. Quick Tip Correlation Analysis.srt 3.1 KB
46. Saving And Loading A Model.mp4 52.6 MB
46. Saving And Loading A Model.srt 9.8 KB
47. Saving And Loading A Model 2.mp4 56.8 MB
47. Saving And Loading A Model 2.srt 9.0 KB
48. Putting It All Together.mp4 150.6 MB
48. Putting It All Together.srt 29.6 KB
48.1 Reading extension Scikit-Learn's Pipeline class explained.html 146 bytes
49. Putting It All Together 2.mp4 116.9 MB
49. Putting It All Together 2.srt 16.1 KB
49.1 Introduction to Scikit-Learn Jupyter Notebook (from the videos).html 197 bytes
49.2 Introduction to Scikit-Learn Jupyter Notebook (with annotations).html 191 bytes
50. Scikit-Learn Practice.html 2.1 KB
car-sales-extended-missing-data.csv 30.2 KB
car-sales-extended.csv 25.7 KB
car-sales-missing-data.csv 287 bytes
heart-disease.csv 11.1 KB
1. Milestone Projects!.html 738 bytes
1. Section Overview.mp4 10.2 MB
1. Section Overview.srt 3.1 KB
2. Project Overview.mp4 34.4 MB
2. Project Overview.srt 10.0 KB
2.1 End-to-end Heart Disease Classification Notebook (with annotations).html 201 bytes
2.2 Structured Data Projects on GitHub.html 155 bytes
2.3 End-to-end Heart Disease Classification Notebook (same as in videos).html 207 bytes
3. Project Environment Setup.mp4 100.8 MB
3. Project Environment Setup.srt 14.4 KB
4. Optional Windows Project Environment Setup.mp4 35.8 MB
4. Optional Windows Project Environment Setup.srt 5.6 KB
5. Step 1~4 Framework Setup.mp4 105.5 MB
5. Step 1~4 Framework Setup.srt 16.6 KB
6. Getting Our Tools Ready.mp4 79.4 MB
6. Getting Our Tools Ready.srt 12.8 KB
7. Exploring Our Data.mp4 66.9 MB
7. Exploring Our Data.srt 11.4 KB
7.1 heart-disease.csv 11.1 KB
8. Finding Patterns.mp4 63.3 MB
8. Finding Patterns.srt 13.4 KB
9. Finding Patterns 2.mp4 99.9 MB
9. Finding Patterns 2.srt 22.3 KB
10. Finding Patterns 3.mp4 137.9 MB
10. Finding Patterns 3.srt 18.9 KB
11. Preparing Our Data For Machine Learning.mp4 72.6 MB
11. Preparing Our Data For Machine Learning.srt 12.0 KB
12. Choosing The Right Models.mp4 96.4 MB
12. Choosing The Right Models.srt 13.0 KB
13. Experimenting With Machine Learning Models.mp4 55.3 MB
13. Experimenting With Machine Learning Models.srt 9.6 KB
14. TuningImproving Our Model.mp4 102.8 MB
14. TuningImproving Our Model.srt 17.6 KB
15. Tuning Hyperparameters.mp4 108.0 MB
15. Tuning Hyperparameters.srt 15.7 KB
16. Tuning Hyperparameters 2.mp4 104.1 MB
16. Tuning Hyperparameters 2.srt 15.1 KB
17. Tuning Hyperparameters 3.mp4 63.0 MB
17. Tuning Hyperparameters 3.srt 9.9 KB
18. Quick Note Confusion Matrix Labels.html 1.1 KB
19. Evaluating Our Model.mp4 71.6 MB
19. Evaluating Our Model.srt 15.1 KB
20. Evaluating Our Model 2.mp4 41.5 MB
20. Evaluating Our Model 2.srt 7.4 KB
21. Evaluating Our Model 3.mp4 64.8 MB
21. Evaluating Our Model 3.srt 11.5 KB
22. Finding The Most Important Features.mp4 127.5 MB
22. Finding The Most Important Features.srt 22.3 KB
23. Reviewing The Project.mp4 86.1 MB
23. Reviewing The Project.srt 13.8 KB
23.1 End-to-end Heart Disease Classification Notebook (with annotations).html 201 bytes
23.2 End-to-end Heart Disease Classification Notebook (same as in videos).html 207 bytes
1. Section Overview.mp4 9.0 MB
1. Section Overview.srt 1.8 KB
2. Project Overview.mp4 32.9 MB
2. Project Overview.srt 6.7 KB
2.1 Structured Data Projects on GitHub.html 155 bytes
2.2 End-to-end Bluebook Bulldozer Regression Notebook (same as in videos).html 214 bytes
2.3 End-to-end Bluebook Bulldozer Regression Notebook (with annotations).html 208 bytes
2.4 Kaggle Bluebook for Bulldozers Competition.html 118 bytes
3. Project Environment Setup.mp4 101.3 MB
3. Project Environment Setup.srt 15.9 KB
4. Step 1~4 Framework Setup.mp4 85.7 MB
4. Step 1~4 Framework Setup.srt 12.4 KB
5. Downloading the data for the next two projects.html 1.6 KB
6. Exploring Our Data.mp4 137.8 MB
6. Exploring Our Data.srt 20.0 KB
7. Exploring Our Data 2.mp4 52.0 MB
7. Exploring Our Data 2.srt 8.6 KB
8. Feature Engineering.mp4 159.1 MB
8. Feature Engineering.srt 22.1 KB
9. Turning Data Into Numbers.mp4 146.2 MB
9. Turning Data Into Numbers.srt 22.3 KB
10. Filling Missing Numerical Values.mp4 106.3 MB
10. Filling Missing Numerical Values.srt 16.9 KB
10.1 Pandas Categorical Datatype Documentation.html 143 bytes
11. Filling Missing Categorical Values.mp4 66.9 MB
11. Filling Missing Categorical Values.srt 11.2 KB
12. Fitting A Machine Learning Model.mp4 55.5 MB
12. Fitting A Machine Learning Model.srt 10.5 KB
13. Splitting Data.mp4 82.7 MB
13. Splitting Data.srt 13.5 KB
14. Challenge What's wrong with splitting data after filling it.html 1.7 KB
15. Custom Evaluation Function.mp4 103.4 MB
15. Custom Evaluation Function.srt 16.1 KB
16. Reducing Data.mp4 93.5 MB
16. Reducing Data.srt 14.6 KB
17. RandomizedSearchCV.mp4 85.8 MB
17. RandomizedSearchCV.srt 12.7 KB
18. Improving Hyperparameters.mp4 79.3 MB
18. Improving Hyperparameters.srt 11.0 KB
19. Preproccessing Our Data.mp4 139.3 MB
19. Preproccessing Our Data.srt 17.8 KB
20. Making Predictions.mp4 79.2 MB
20. Making Predictions.srt 11.4 KB
21. Feature Importance.mp4 142.3 MB
21. Feature Importance.srt 17.3 KB
21.1 End-to-end Bluebook Bulldozer Regression Notebook (with annotations).html 208 bytes
21.2 End-to-end Bluebook Bulldozer Regression Notebook (same as in videos).html 214 bytes
1. Data Engineering Introduction.mp4 13.5 MB
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2. What Is Data.mp4 42.2 MB
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2.1 Kaggle.html 92 bytes
3. What Is A Data Engineer.mp4 15.2 MB
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4. What Is A Data Engineer 2.mp4 24.2 MB
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5. What Is A Data Engineer 3.mp4 24.3 MB
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6. What Is A Data Engineer 4.mp4 14.9 MB
6. What Is A Data Engineer 4.srt 3.9 KB
7. Types Of Databases.mp4 32.6 MB
7. Types Of Databases.srt 8.4 KB
7.1 OLTP vs OLAP.html 126 bytes
7.2 A Primer on ACID Transactions.html 117 bytes
8. Quick Note Upcoming Video.html 481 bytes
9. Optional OLTP Databases.mp4 79.7 MB
9. Optional OLTP Databases.srt 12.1 KB
10. Optional Learn SQL.html 410 bytes
11. Hadoop, HDFS and MapReduce.mp4 10.1 MB
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12. Apache Spark and Apache Flink.mp4 5.8 MB
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13. Kafka and Stream Processing.mp4 19.2 MB
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1. Section Overview.mp4 12.2 MB
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2. Deep Learning and Unstructured Data.mp4 102.0 MB
2. Deep Learning and Unstructured Data.srt 20.2 KB
3. Setting Up With Google.html 568 bytes
4. Setting Up Google Colab.mp4 74.2 MB
4. Setting Up Google Colab.srt 9.6 KB
4.1 Kaggle Dog Breed Identification Competition (the basis of our upcoming project).html 119 bytes
4.2 Google Colab (our workspace for the upcoming project).html 95 bytes
4.3 Google Colab IO example (how to get data in and out of your Colab notebook).html 113 bytes
4.4 Introduction to Google Colab example notebook.html 116 bytes
4.5 End-to-end Dog Vision Notebook (the project we'll be working through).html 182 bytes
5. Google Colab Workspace.mp4 39.6 MB
5. Google Colab Workspace.srt 6.3 KB
5.1 Google Colab FAQ (things you should know about Google Colab).html 110 bytes
5.2 Google Colab (our workspace for the upcoming project).html 95 bytes
6. Uploading Project Data.mp4 52.0 MB
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6.1 Kaggle Dog Breed Identification Competition Data.html 115 bytes
6.2 Google Colab IO example (how to get data in and out of your Colab notebook).html 113 bytes
7. Setting Up Our Data.mp4 42.3 MB
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8. Setting Up Our Data 2.mp4 20.9 MB
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9. Importing TensorFlow 2.mp4 116.8 MB
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10. Optional TensorFlow 2.0 Default Issue.mp4 28.1 MB
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10.1 Loading TensorFlow 2.0 into a Colab Notebook (if it isn't the default).html 129 bytes
11. Using A GPU.mp4 80.6 MB
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11.1 Google Colab example GPU usage.html 114 bytes
12. Optional GPU and Google Colab.mp4 45.9 MB
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12.1 Introduction to Google Colab example notebook.html 116 bytes
12.2 Google Colab Example of GPU speed up versus CPU.html 114 bytes
13. Optional Reloading Colab Notebook.mp4 88.7 MB
13. Optional Reloading Colab Notebook.srt 7.8 KB
14. Loading Our Data Labels.mp4 114.8 MB
14. Loading Our Data Labels.srt 16.1 KB
14.1 Documentation on how many images Google recommends for image problems.html 129 bytes
15. Preparing The Images.mp4 133.9 MB
15. Preparing The Images.srt 15.1 KB
16. Turning Data Labels Into Numbers.mp4 107.5 MB
16. Turning Data Labels Into Numbers.srt 13.8 KB
17. Creating Our Own Validation Set.mp4 66.4 MB
17. Creating Our Own Validation Set.srt 11.3 KB
17.1 Blog post by Rachel Thomas (of fast.ai) on how and why you should create a validation set.html 108 bytes
18. Preprocess Images.mp4 90.1 MB
18. Preprocess Images.srt 12.9 KB
18.1 Documentation for loading images in TensorFlow.html 114 bytes
18.2 TensorFlow guidelines for loading all kinds of data (turning your data into Tensors).html 98 bytes
19. Preprocess Images 2.mp4 105.1 MB
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20. Turning Data Into Batches.mp4 87.8 MB
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21. Turning Data Into Batches 2.mp4 149.4 MB
21. Turning Data Into Batches 2.srt 20.2 KB
21.1 Yann LeCun's (OG of deep learning) Tweet on Batch Sizes.html 118 bytes
22. Visualizing Our Data.mp4 122.0 MB
22. Visualizing Our Data.srt 15.7 KB
23. Preparing Our Inputs and Outputs.mp4 50.1 MB
23. Preparing Our Inputs and Outputs.srt 7.8 KB
23.1 TensorFlow Hub (resource for pre-trained deep learning models and more).html 79 bytes
24. Optional How machines learn and what's going on behind the scenes.html 2.7 KB
25. Building A Deep Learning Model.mp4 121.9 MB
25. Building A Deep Learning Model.srt 15.9 KB
25.1 Andrei Karpathy's talk on AI at Tesla.html 95 bytes
25.2 Papers with Code (a great resource for some of the best machine learning papers with code examples).html 88 bytes
25.3 MobileNetV2 (the model we're using) on TensorFlow Hub.html 132 bytes
25.4 PyTorch Hub (PyTorch version of TensorFlow Hub).html 85 bytes
25.5 TensorFlow Hub (resource for pre-trained deep learning models and more).html 79 bytes
26. Building A Deep Learning Model 2.mp4 105.9 MB
26. Building A Deep Learning Model 2.srt 12.5 KB
26.1 Keras in TensorFlow Overview Documentation.html 108 bytes
27. Building A Deep Learning Model 3.mp4 105.9 MB
27. Building A Deep Learning Model 3.srt 11.2 KB
27.1 The Softmax Function (activation function we use in our model).html 107 bytes
27.2 Step by step breakdown of a convolutional neural network (what MobileNetV2 is made of).html 172 bytes
27.3 MobileNetV2 (the model we're using) architecture explanation by Sik-Ho Tsang.html 163 bytes
28. Building A Deep Learning Model 4.mp4 86.3 MB
28. Building A Deep Learning Model 4.srt 12.0 KB
28.1 [Article] How to choose loss & activation functions when building a deep learning model.html 169 bytes
29. Summarizing Our Model.mp4 45.4 MB
29. Summarizing Our Model.srt 6.0 KB
30. Evaluating Our Model.mp4 79.3 MB
30. Evaluating Our Model.srt 10.4 KB
30.1 TensorBoard Callback Documentation.html 134 bytes
31. Preventing Overfitting.mp4 36.5 MB
31. Preventing Overfitting.srt 5.5 KB
31.1 Early Stopping Callback (a way to stop your model from training when it stops improving) Documentation.html 136 bytes
32. Training Your Deep Neural Network.mp4 166.6 MB
32. Training Your Deep Neural Network.srt 23.1 KB
33. Evaluating Performance With TensorBoard.mp4 74.2 MB
33. Evaluating Performance With TensorBoard.srt 9.6 KB
34. Make And Transform Predictions.mp4 155.0 MB
34. Make And Transform Predictions.srt 19.2 KB
35. Transform Predictions To Text.mp4 129.9 MB
35. Transform Predictions To Text.srt 17.6 KB
35.1 TensorFlow documentation for the unbatch() function.html 127 bytes
36. Visualizing Model Predictions.mp4 119.3 MB
36. Visualizing Model Predictions.srt 17.0 KB
37. Visualizing And Evaluate Model Predictions 2.mp4 143.8 MB
37. Visualizing And Evaluate Model Predictions 2.srt 17.6 KB
38. Visualizing And Evaluate Model Predictions 3.mp4 113.2 MB
38. Visualizing And Evaluate Model Predictions 3.srt 13.8 KB
39. Saving And Loading A Trained Model.mp4 127.0 MB
39. Saving And Loading A Trained Model.srt 16.9 KB
40. Training Model On Full Dataset.mp4 139.8 MB
40. Training Model On Full Dataset.srt 19.2 KB
41. Making Predictions On Test Images.mp4 140.8 MB
41. Making Predictions On Test Images.srt 20.3 KB
41.1 Dog Vision Prediction Probabilities Array.html 170 bytes
42. Submitting Model to Kaggle.mp4 121.3 MB
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42.1 Dog Vision Predictions with MobileNetV2 Ready for Kaggle Submission.html 180 bytes
43. Making Predictions On Our Images.mp4 119.2 MB
43. Making Predictions On Our Images.srt 18.6 KB
43.1 End-to-end Dog Vision Notebook (with annotations).html 185 bytes
43.2 End-to-end Dog Vision Notebook (from the videos).html 191 bytes
44. Finishing Dog Vision Where to next.html 3.9 KB
1. Section Overview.mp4 10.9 MB
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2. Communicating Your Work.mp4 20.2 MB
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3. Communicating With Managers.mp4 18.4 MB
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6. Communicating With Outside World.mp4 14.5 MB
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6.1 fast_template by fast.ai (a template you can use for your blog on GitHub Pages).html 106 bytes
6.2 Devblog by Hashnode (an easy and free way to create a blog you own).html 89 bytes
7. Storytelling.mp4 12.0 MB
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8. Communicating and sharing your work Further reading.html 3.1 KB
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2. Quick Note Upcoming Video.html 587 bytes
3. What If I Don't Have Enough Experience.mp4 161.0 MB
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4. Learning Guideline.html 325 bytes
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6. JTS Learn to Learn.mp4 11.1 MB
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9. CWD Git + Github.mp4 176.1 MB
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10. CWD Git + Github 2.mp4 118.4 MB
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11. Contributing To Open Source.mp4 130.3 MB
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12. Contributing To Open Source 2.mp4 113.1 MB
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13. Coding Challenges.html 948 bytes
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1. What Is A Programming Language.mp4 104.8 MB
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2. Python Interpreter.mp4 78.0 MB
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2.1 python.org.html 84 bytes
3. How To Run Python Code.mp4 52.9 MB
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4. Our First Python Program.mp4 47.2 MB
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5. Latest Version Of Python.mp4 10.7 MB
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6. Python 2 vs Python 3.mp4 69.5 MB
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6.1 Python 2 vs Python 3.html 128 bytes
6.2 The Story of Python.html 104 bytes
6.3 Python 2 vs Python 3 - another one.html 161 bytes
7. Exercise How Does Python Work.mp4 26.0 MB
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8. Learning Python.mp4 38.5 MB
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9. Python Data Types.mp4 28.8 MB
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10. How To Succeed.html 280 bytes
11. Numbers.mp4 72.7 MB
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11.1 Floating point numbers.html 104 bytes
12. Math Functions.mp4 41.8 MB
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13. DEVELOPER FUNDAMENTALS I.mp4 59.7 MB
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14. Operator Precedence.mp4 14.4 MB
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14.1 Exercise Repl.html 106 bytes
15. Exercise Operator Precedence.html 683 bytes
15.1 Exercise Repl.html 106 bytes
16. Optional bin() and complex.mp4 21.9 MB
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16.1 Base Numbers.html 111 bytes
17. Variables.mp4 93.6 MB
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18. Expressions vs Statements.mp4 11.0 MB
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19. Augmented Assignment Operator.mp4 15.3 MB
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19.1 Exercise Repl.html 116 bytes
20. Strings.mp4 31.0 MB
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21. String Concatenation.mp4 7.3 MB
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22. Type Conversion.mp4 19.0 MB
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23. Escape Sequences.mp4 23.2 MB
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24. Formatted Strings.mp4 49.3 MB
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26. Immutability.mp4 20.8 MB
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27. Built-In Functions + Methods.mp4 69.4 MB
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27.1 String Methods.html 115 bytes
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28. Booleans.mp4 16.5 MB
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29. Exercise Type Conversion.mp4 50.3 MB
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30. DEVELOPER FUNDAMENTALS II.mp4 29.2 MB
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30.1 Python Comments Best Practices.html 106 bytes
31. Exercise Password Checker.mp4 51.1 MB
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32. Lists.mp4 22.0 MB
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33. List Slicing.mp4 49.9 MB
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34. Matrix.mp4 19.1 MB
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35. List Methods.mp4 61.8 MB
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35.1 List Methods.html 113 bytes
36. List Methods 2.mp4 27.4 MB
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36.1 Python Keywords.html 117 bytes
36.2 Exercise Repl.html 94 bytes
37. List Methods 3.mp4 27.7 MB
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38. Common List Patterns.mp4 40.5 MB
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38.1 Exercise Repl.html 94 bytes
39. List Unpacking.mp4 13.9 MB
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40. None.mp4 7.9 MB
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41. Dictionaries.mp4 32.7 MB
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42. DEVELOPER FUNDAMENTALS III.mp4 26.6 MB
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43. Dictionary Keys.mp4 20.4 MB
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44. Dictionary Methods.mp4 27.2 MB
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44.1 Dictionary Methods.html 119 bytes
45. Dictionary Methods 2.mp4 42.4 MB
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45.1 Exercise Repl.html 97 bytes
46. Tuples.mp4 25.6 MB
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47. Tuples 2.mp4 17.0 MB
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47.1 Tuple Methods.html 114 bytes
48. Sets.mp4 37.0 MB
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49. Sets 2.mp4 64.3 MB
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49.1 Exercise Repl.html 91 bytes
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1. Breaking The Flow.mp4 20.3 MB
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2. Conditional Logic.mp4 74.6 MB
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3. Indentation In Python.mp4 28.0 MB
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4. Truthy vs Falsey.mp4 42.8 MB
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4.1 Truthy vs Falsey Stackoverflow.html 170 bytes
5. Ternary Operator.mp4 19.7 MB
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6. Short Circuiting.mp4 19.4 MB
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7. Logical Operators.mp4 28.3 MB
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8. Exercise Logical Operators.mp4 46.6 MB
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9. is vs ==.mp4 33.6 MB
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10. For Loops.mp4 34.3 MB
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11. Iterables.mp4 43.2 MB
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12. Exercise Tricky Counter.mp4 16.4 MB
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13. range().mp4 28.3 MB
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14. enumerate().mp4 24.8 MB
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17. break, continue, pass.mp4 22.2 MB
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18. Our First GUI.mp4 49.6 MB
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18.1 Exercise Repl.html 99 bytes
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19. DEVELOPER FUNDAMENTALS IV.mp4 50.2 MB
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20. Exercise Find Duplicates.mp4 20.3 MB
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21. Functions.mp4 48.6 MB
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24. return.mp4 63.0 MB
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26. Methods vs Functions.mp4 30.7 MB
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27. Docstrings.mp4 17.3 MB
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28. Clean Code.mp4 19.7 MB
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29. args and kwargs.mp4 43.0 MB
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31. Scope.mp4 20.1 MB
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44. Python Exam Testing Your Understanding.html 1.1 KB
45. Modules in Python.mp4 82.2 MB
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46. Quick Note Upcoming Videos.html 448 bytes
47. Optional PyCharm.mp4 53.1 MB
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48. Packages in Python.mp4 72.4 MB
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49. Different Ways To Import.mp4 48.0 MB
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50. Next Steps.html 959 bytes
51. Bonus Resource Python Cheatsheet.html 489 bytes
1. Statistics and Mathematics.html 710 bytes
1. Become An Alumni.html 944 bytes
2. Thank You.mp4 11.1 MB
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3. Course Review.html 169 bytes
4. The Final Challenge.html 169 bytes
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