Видео курса

  • Урок 1. 00:04:41
    Outline and Motivation
  • Урок 2. 00:02:05
    Where to get the Code and Data
  • Урок 3. 00:03:16
    All Data is the Same
  • Урок 4. 00:02:12
    Plug-and-Play
  • Урок 5. 00:06:38
    Bias-Variance Key Terms
  • Урок 6. 00:03:10
    Bias-Variance Trade-Off
  • Урок 7. 00:03:34
    Bias-Variance Decomposition
  • Урок 8. 00:18:09
    Polynomial Regression Demo
  • Урок 9. 00:06:33
    K-Nearest Neighbor and Decision Tree Demo
  • Урок 10. 00:04:27
    Cross-Validation as a Method for Optimizing Model Complexity
  • Урок 11. 00:09:56
    Bootstrap Estimation
  • Урок 12. 00:05:21
    Bootstrap Demo
  • Урок 13. 00:02:37
    Bagging
  • Урок 14. 00:07:20
    Bagging Regression Trees
  • Урок 15. 00:08:40
    Bagging Classification Trees
  • Урок 16. 00:03:55
    Stacking
  • Урок 17. 00:08:55
    Random Forest Algorithm
  • Урок 18. 00:07:06
    Random Forest Regressor
  • Урок 19. 00:04:57
    Random Forest Classifier
  • Урок 20. 00:03:48
    Random Forest vs Bagging Trees
  • Урок 21. 00:04:14
    Implementing a "Not as Random" Forest
  • Урок 22. 00:02:39
    Connection to Deep Learning: Dropout
  • Урок 23. 00:07:10
    AdaBoost Algorithm
  • Урок 24. 00:01:51
    Additive Modeling
  • Урок 25. 00:07:16
    AdaBoost Loss Function: Exponential Loss
  • Урок 26. 00:08:27
    AdaBoost Implementation
  • Урок 27. 00:03:30
    Comparison to Stacking
  • Урок 28. 00:03:49
    Connection to Deep Learning
  • Урок 29. 00:04:56
    Summary and What's Next
  • Урок 30. 00:02:49
    What is the Appendix?
  • Урок 31. 00:10:12
    Confidence Intervals
  • Урок 32. 00:20:21
    Windows-Focused Environment Setup 2018
  • Урок 33. 00:17:33
    How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow
  • Урок 34. 00:15:55
    How to Code by Yourself (part 1)
  • Урок 35. 00:09:24
    How to Code by Yourself (part 2)
  • Урок 36. 00:10:25
    How to Succeed in this Course (Long Version)
  • Урок 37. 00:22:05
    Is this for Beginners or Experts? Academic or Practical? Fast or slow-paced?
  • Урок 38. 00:12:30
    Proof that using Jupyter Notebook is the same as not using it
  • Урок 39. 00:02:21
    BONUS: Where to get Udemy coupons and FREE deep learning material
  • Урок 40. 00:04:39
    Python 2 vs Python 3
  • Урок 41. 00:11:20
    What order should I take your courses in? (part 1)
  • Урок 42. 00:16:08
    What order should I take your courses in? (part 2)
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