FreeCoursesOnline Me Packt Python Machine Learning Tips Tricks and Techniques FCO

1. 01 - The Course Overview.mp427.02MB
2. 02 - Using Feature Scaling to Standardize Data.mp437.45MB
3. 03 - Implementing Feature Engineering with Logistic Regression.mp411.62MB
4. 04 - Extracting Data with Feature Selection and Interaction.mp421.92MB
5. 05 - Combining All Together.mp413.06MB
6. 06 - Build Model Based on Real-World Problems.mp414.56MB
7. 07 - Support Vector Machines.mp423.28MB
8. 08 - Implementing kNN on the Data Set.mp434.24MB
9. 09 - Decision Tree as Predictive Model.mp427.09MB
10. 10 - Tricks with Dimensionality Reduction.mp420.5MB
11. 11 - Combining All Together.mp421.3MB
12. 12 - Random Forest for Classification.mp423.87MB
13. 13 - Gradient Boosting Trees and Bayes Optimization.mp433.36MB
14. 14 - CatBoost to Handle Categorical Data.mp420.1MB
15. 15 - Implement Blending.mp427.4MB
16. 16 - Implement Stacking.mp431.2MB
17. 17 - Memory-Based Collaborative Filtering.mp421.33MB
18. 18 - Item-to-Item Recommendation with kNN.mp421.22MB
19. 19 - Applying Matrix Factorization on Datasets.mp427.5MB
20. 20 - Wordbatch for Real-World Problem.mp423.25MB
21. 21 - Validation Dataset Tuning.mp422.12MB
22. 22 - Regularizing Model to Avoid Overfitting.mp414.6MB
23. 23 - Adversarial Validation.mp419.97MB
24. 24 - Perform Metric Selection on Real Data.mp4220.23MB