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[Volver] Parent Directory - [TXT] 47. Scikit-Learn Practice.html 2.1K [TXT] 46. Putting It All Together 2.srt 16K [VID] 46. Putting It All Together 2.mp4 117M [TXT] 46.2 Introduction to Scikit-Learn Jupyter Notebook (with annotations).html 191 [TXT] 46.1 Introduction to Scikit-Learn Jupyter Notebook (from the videos).html 197 [TXT] 45. Putting It All Together.srt 26K [VID] 45. Putting It All Together.mp4 158M [TXT] 44. Saving And Loading A Model 2.srt 9.0K [VID] 44. Saving And Loading A Model 2.mp4 57M [TXT] 43. Saving And Loading A Model.srt 9.8K [VID] 43. Saving And Loading A Model.mp4 53M [TXT] 42. Quick Tip Correlation Analysis.srt 3.1K [VID] 42. Quick Tip Correlation Analysis.mp4 17M [TXT] 41. Tuning Hyperparameters 3.srt 19K [VID] 41. Tuning Hyperparameters 3.mp4 122M [TXT] 40. Tuning Hyperparameters 2.srt 17K [VID] 40. Tuning Hyperparameters 2.mp4 117M [TXT] 39. Tuning Hyperparameters.srt 31K [VID] 39. Tuning Hyperparameters.mp4 176M [TXT] 38. Improving A Machine Learning Model.srt 15K [VID] 38. Improving A Machine Learning Model.mp4 91M [TXT] 37. Evaluating A Model With Scikit-learn Functions.srt 16K [VID] 37. Evaluating A Model With Scikit-learn Functions.mp4 95M [TXT] 36. Evaluating A Model With Cross Validation and Scoring Parameter.srt 18K [VID] 36. Evaluating A Model With Cross Validation and Scoring Parameter.mp4 92M [TXT] 35. Machine Learning Model Evaluation.html 7.1K [   ] 34. Evaluating A Regression Model 3 (MSE).srt 9.2K [VID] 34. Evaluating A Regression Model 3 (MSE).mp4 55M [TXT] 33. Evaluating A Regression Model 2 (MAE).srt 5.7K [VID] 33. Evaluating A Regression Model 2 (MAE).mp4 29M [TXT] 32. Evaluating A Regression Model 1 (R2 Score).srt 12K [VID] 32. Evaluating A Regression Model 1 (R2 Score).mp4 70M [TXT] 31. Evaluating A Classification Model 6 (Classification Report).srt 15K [VID] 31. Evaluating A Classification Model 6 (Classification Report).mp4 87M [TXT] 30. Evaluating A Classification Model 5 (Confusion Matrix).srt 11K [VID] 30. Evaluating A Classification Model 5 (Confusion Matrix).mp4 64M [TXT] 29. Evaluating A Classification Model 4 (Confusion Matrix).srt 15K [VID] 29. Evaluating A Classification Model 4 (Confusion Matrix).mp4 78M [TXT] 28. Evaluating A Classification Model 3 (ROC Curve).srt 10K [VID] 28. Evaluating A Classification Model 3 (ROC Curve).mp4 51M [TXT] 27. Evaluating A Classification Model 2 (ROC Curve).srt 12K [VID] 27. Evaluating A Classification Model 2 (ROC Curve).mp4 66M [TXT] 26. Evaluating A Classification Model 1 (Accuracy).srt 5.9K [VID] 26. Evaluating A Classification Model 1 (Accuracy).mp4 31M [TXT] 25. Evaluating A Machine Learning Model 2 (Cross Validation).srt 17K [VID] 25. Evaluating A Machine Learning Model 2 (Cross Validation).mp4 96M [TXT] 24. Evaluating A Machine Learning Model (Score).srt 13K [VID] 24. Evaluating A Machine Learning Model (Score).mp4 87M [TXT] 23. Making Predictions With Our Model (Regression).srt 9.1K [VID] 23. Making Predictions With Our Model (Regression).mp4 45M [TXT] 22. predict() vs predict_proba().srt 12K [VID] 22. predict() vs predict_proba().mp4 54M [   ] 21. Making Predictions With Our Model.srt 67M [VID] 21. Making Predictions With Our Model.mp4 67M [TXT] 20. Fitting A Model To The Data.srt 9.3K [VID] 20. Fitting A Model To The Data.mp4 57M [TXT] 19. Choosing The Right Model For Your Data 3 (Classification).srt 17K [VID] 19. Choosing The Right Model For Your Data 3 (Classification).mp4 119M [TXT] 18. Quick Tip How ML Algorithms Work.srt 1.9K [VID] 18. Quick Tip How ML Algorithms Work.mp4 11M [TXT] 17. Quick Note Decision Trees.html 221 [TXT] 16. Choosing The Right Model For Your Data 2 (Regression).srt 12K [VID] 16. Choosing The Right Model For Your Data 2 (Regression).mp4 87M [TXT] 15. Choosing The Right Model For Your Data.srt 21K [VID] 15. Choosing The Right Model For Your Data.mp4 143M [TXT] 15.1 Scikit-Learn machine learning map (how to choose the right machine learning model).html 133 [TXT] 14. Getting Your Data Ready Handling Missing Values With Scikit-learn.srt 23K [VID] 14. Getting Your Data Ready Handling Missing Values With Scikit-learn.mp4 137M [TXT] 13. Note Correction in the upcoming video (splitting data).html 2.2K [TXT] 12. Getting Your Data Ready Handling Missing Values With Pandas.srt 17K [VID] 12. Getting Your Data Ready Handling Missing Values With Pandas.mp4 105M [TXT] 11. Getting Your Data Ready Convert Data To Numbers.srt 23K [VID] 11. Getting Your Data Ready Convert Data To Numbers.mp4 135M [TXT] 10. Quick Tip Clean, Transform, Reduce.srt 6.4K [VID] 10. Quick Tip Clean, Transform, Reduce.mp4 17M [TXT] 9. Getting Your Data Ready Splitting Your Data.srt 12K [VID] 9. Getting Your Data Ready Splitting Your Data.mp4 64M [Fichero comrpimido] 9.1 scikit-learn-data.zip 21K [TXT] 8. Optional Debugging Warnings In Jupyter.srt 26K [VID] 8. Optional Debugging Warnings In Jupyter.mp4 176M [TXT] 7. Typical scikit-learn Workflow.srt 32K [VID] 7. Typical scikit-learn Workflow.mp4 190M [TXT] 7.1 Example Scikit-Learn Workflow Notebook.html 192 [TXT] 6. Scikit-learn Cheatsheet.srt 10K [VID] 6. Scikit-learn Cheatsheet.mp4 75M [TXT] 6.1 Scikit-Learn Reference Notebook.html 194 [TXT] 5. Quick Note Upcoming Videos.html 1.0K [TXT] 4. Refresher What Is Machine Learning.srt 6.3K [VID] 4. Refresher What Is Machine Learning.mp4 88M [TXT] 3. Quick Note Upcoming Video.html 390 [TXT] 2. Scikit-learn Introduction.srt 11K [VID] 2. Scikit-learn Introduction.mp4 41M [TXT] 2.3 Introduction to Scikit-Learn Jupyter Notebook (with annotations).html 191 [TXT] 2.2 Introduction to Scikit-Learn Jupyter Notebook (from the upcoming videos).html 197 [TXT] 2.1 Scikit-Learn Documentation.html 108 [TXT] 1. Section Overview.srt 4.1K [VID] 1. Section Overview.mp4 12M

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