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[Tutorialsplanet.NET] Udemy - Ensemble Machine Learning in Python Random Forest, AdaBoost

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视频 2020-8-28 02:03 2024-12-14 06:00 131 884.95 MB 43
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文件列表
  1. 1. Get Started/1. Outline and Motivation.mp47.19MB
  2. 1. Get Started/2. Where to get the Code and Data.mp43.36MB
  3. 1. Get Started/3. All Data is the Same.mp45.24MB
  4. 1. Get Started/4. Plug-and-Play.mp43.5MB
  5. 10. Appendix FAQ/1. What is the Appendix.mp45.46MB
  6. 10. Appendix FAQ/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp437.84MB
  7. 2. Bias-Variance Trade-Off/1. Bias-Variance Key Terms.mp410.24MB
  8. 2. Bias-Variance Trade-Off/2. Bias-Variance Trade-Off.mp44.89MB
  9. 2. Bias-Variance Trade-Off/3. Bias-Variance Decomposition.mp414.3MB
  10. 2. Bias-Variance Trade-Off/4. Polynomial Regression Demo.mp441.76MB
  11. 2. Bias-Variance Trade-Off/5. K-Nearest Neighbor and Decision Tree Demo.mp413.86MB
  12. 2. Bias-Variance Trade-Off/6. Cross-Validation as a Method for Optimizing Model Complexity.mp46.98MB
  13. 2. Bias-Variance Trade-Off/7. Suggestion Box.mp416.12MB
  14. 3. Bootstrap Estimates and Bagging/1. Bootstrap Estimation.mp447.73MB
  15. 3. Bootstrap Estimates and Bagging/2. Bootstrap Demo.mp410.96MB
  16. 3. Bootstrap Estimates and Bagging/3. Bagging.mp43.93MB
  17. 3. Bootstrap Estimates and Bagging/4. Bagging Regression Trees.mp415.88MB
  18. 3. Bootstrap Estimates and Bagging/5. Bagging Classification Trees.mp420.32MB
  19. 3. Bootstrap Estimates and Bagging/6. Stacking.mp46.08MB
  20. 4. Random Forest/1. Random Forest Algorithm.mp414.43MB
  21. 4. Random Forest/2. Random Forest Regressor.mp414.9MB
  22. 4. Random Forest/3. Random Forest Classifier.mp412.58MB
  23. 4. Random Forest/4. Random Forest vs Bagging Trees.mp47.82MB
  24. 4. Random Forest/5. Implementing a Not as Random Forest.mp48.69MB
  25. 4. Random Forest/6. Connection to Deep Learning Dropout.mp44.22MB
  26. 5. AdaBoost/1. AdaBoost Algorithm.mp410.88MB
  27. 5. AdaBoost/2. Additive Modeling.mp42.81MB
  28. 5. AdaBoost/3. AdaBoost Loss Function Exponential Loss.mp411.19MB
  29. 5. AdaBoost/4. AdaBoost Implementation.mp415.79MB
  30. 5. AdaBoost/5. Comparison to Stacking.mp45.44MB
  31. 5. AdaBoost/6. Connection to Deep Learning.mp46.03MB
  32. 5. AdaBoost/7. Summary and What's Next.mp47.37MB
  33. 6. Background Review/1. Confidence Intervals.mp412.6MB
  34. 7. Setting Up Your Environment/1. Windows-Focused Environment Setup 2018.mp4186.3MB
  35. 7. Setting Up Your Environment/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp443.92MB
  36. 8. Extra Help With Python Coding for Beginners/1. How to Code by Yourself (part 1).mp424.54MB
  37. 8. Extra Help With Python Coding for Beginners/2. How to Code by Yourself (part 2).mp414.8MB
  38. 8. Extra Help With Python Coding for Beginners/3. Proof that using Jupyter Notebook is the same as not using it.mp478.26MB
  39. 8. Extra Help With Python Coding for Beginners/4. Python 2 vs Python 3.mp47.83MB
  40. 9/1. How to Succeed in this Course (Long Version).mp413MB
  41. 9/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp438.96MB
  42. 9/3. What order should I take your courses in (part 1).mp429.33MB
  43. 9/4. What order should I take your courses in (part 2).mp437.63MB
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