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

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  • 文件大小:1GB
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  • 最近下载:2021-01-10 21:35:49
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文件列表

  1. 6. Appendix FAQ/3. Windows-Focused Environment Setup 2018.mp4 186MB
  2. 6. Appendix FAQ/9. Proof that using Jupyter Notebook is the same as not using it.mp4 78MB
  3. 3. Bootstrap Estimates and Bagging/1. Bootstrap Estimation.mp4 48MB
  4. 6. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 44MB
  5. 2. Bias-Variance Trade-Off/4. Polynomial Regression Demo.mp4 42MB
  6. 6. Appendix FAQ/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39MB
  7. 6. Appendix FAQ/13. BONUS Where to get Udemy coupons and FREE deep learning material.srt 38MB
  8. 6. Appendix FAQ/13. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 38MB
  9. 6. Appendix FAQ/12. What order should I take your courses in (part 2).mp4 38MB
  10. 3. Bootstrap Estimates and Bagging/1. Bootstrap Estimation.srt 30MB
  11. 6. Appendix FAQ/11. What order should I take your courses in (part 1).mp4 29MB
  12. 6. Appendix FAQ/5. How to Code by Yourself (part 1).mp4 25MB
  13. 3. Bootstrap Estimates and Bagging/5. Bagging Classification Trees.mp4 20MB
  14. 4. Random Forest/6. Connection to Deep Learning Dropout.srt 19MB
  15. 5. AdaBoost/4. AdaBoost Implementation.srt 19MB
  16. 4. Random Forest/1. Random Forest Algorithm.srt 17MB
  17. 3. Bootstrap Estimates and Bagging/4. Bagging Regression Trees.mp4 16MB
  18. 5. AdaBoost/4. AdaBoost Implementation.mp4 16MB
  19. 4. Random Forest/2. Random Forest Regressor.mp4 15MB
  20. 6. Appendix FAQ/6. How to Code by Yourself (part 2).mp4 15MB
  21. 4. Random Forest/1. Random Forest Algorithm.mp4 14MB
  22. 2. Bias-Variance Trade-Off/3. Bias-Variance Decomposition.mp4 14MB
  23. 3. Bootstrap Estimates and Bagging/5. Bagging Classification Trees.srt 14MB
  24. 2. Bias-Variance Trade-Off/5. K-Nearest Neighbor and Decision Tree Demo.srt 14MB
  25. 2. Bias-Variance Trade-Off/5. K-Nearest Neighbor and Decision Tree Demo.mp4 14MB
  26. 6. Appendix FAQ/7. How to Succeed in this Course (Long Version).mp4 13MB
  27. 6. Appendix FAQ/2. Confidence Intervals.mp4 13MB
  28. 4. Random Forest/3. Random Forest Classifier.mp4 13MB
  29. 5. AdaBoost/3. AdaBoost Loss Function Exponential Loss.mp4 11MB
  30. 3. Bootstrap Estimates and Bagging/2. Bootstrap Demo.mp4 11MB
  31. 5. AdaBoost/1. AdaBoost Algorithm.mp4 11MB
  32. 2. Bias-Variance Trade-Off/1. Bias-Variance Key Terms.mp4 10MB
  33. 4. Random Forest/5. Implementing a Not as Random Forest.mp4 9MB
  34. 6. Appendix FAQ/10. Python 2 vs Python 3.mp4 8MB
  35. 4. Random Forest/4. Random Forest vs Bagging Trees.mp4 8MB
  36. 5. AdaBoost/7. Summary and What's Next.mp4 7MB
  37. 1. Get Started/1. Outline and Motivation.mp4 7MB
  38. 2. Bias-Variance Trade-Off/6. Cross-Validation as a Method for Optimizing Model Complexity.mp4 7MB
  39. 3. Bootstrap Estimates and Bagging/6. Stacking.mp4 6MB
  40. 5. AdaBoost/6. Connection to Deep Learning.mp4 6MB
  41. 6. Appendix FAQ/1. What is the Appendix.mp4 5MB
  42. 5. AdaBoost/5. Comparison to Stacking.mp4 5MB
  43. 6. Appendix FAQ/7. How to Succeed in this Course (Long Version).srt 5MB
  44. 1. Get Started/3. All Data is the Same.mp4 5MB
  45. 2. Bias-Variance Trade-Off/2. Bias-Variance Trade-Off.mp4 5MB
  46. 4. Random Forest/6. Connection to Deep Learning Dropout.mp4 4MB
  47. 3. Bootstrap Estimates and Bagging/3. Bagging.srt 4MB
  48. 3. Bootstrap Estimates and Bagging/3. Bagging.mp4 4MB
  49. 1. Get Started/4. Plug-and-Play.mp4 4MB
  50. 1. Get Started/2. Where to get the Code and Data.mp4 3MB
  51. 5. AdaBoost/2. Additive Modeling.mp4 3MB
  52. 6. Appendix FAQ/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 32KB
  53. 6. Appendix FAQ/12. What order should I take your courses in (part 2).srt 23KB
  54. 6. Appendix FAQ/5. How to Code by Yourself (part 1).srt 23KB
  55. 6. Appendix FAQ/3. Windows-Focused Environment Setup 2018.srt 20KB
  56. 6. Appendix FAQ/11. What order should I take your courses in (part 1).srt 16KB
  57. 6. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14KB
  58. 6. Appendix FAQ/9. Proof that using Jupyter Notebook is the same as not using it.srt 14KB
  59. 2. Bias-Variance Trade-Off/4. Polynomial Regression Demo.srt 13KB
  60. 6. Appendix FAQ/6. How to Code by Yourself (part 2).srt 13KB
  61. 6. Appendix FAQ/2. Confidence Intervals.srt 13KB
  62. 5. AdaBoost/1. AdaBoost Algorithm.srt 9KB
  63. 2. Bias-Variance Trade-Off/1. Bias-Variance Key Terms.srt 9KB
  64. 4. Random Forest/2. Random Forest Regressor.srt 9KB
  65. 5. AdaBoost/3. AdaBoost Loss Function Exponential Loss.srt 8KB
  66. 1. Get Started/1. Outline and Motivation.srt 7KB
  67. 5. AdaBoost/7. Summary and What's Next.srt 6KB
  68. 6. Appendix FAQ/10. Python 2 vs Python 3.srt 6KB
  69. 2. Bias-Variance Trade-Off/6. Cross-Validation as a Method for Optimizing Model Complexity.srt 6KB
  70. 4. Random Forest/3. Random Forest Classifier.srt 6KB
  71. 3. Bootstrap Estimates and Bagging/6. Stacking.srt 5KB
  72. 4. Random Forest/5. Implementing a Not as Random Forest.srt 5KB
  73. 5. AdaBoost/6. Connection to Deep Learning.srt 5KB
  74. 3. Bootstrap Estimates and Bagging/4. Bagging Regression Trees.srt 5KB
  75. 1. Get Started/3. All Data is the Same.srt 4KB
  76. 4. Random Forest/4. Random Forest vs Bagging Trees.srt 4KB
  77. 5. AdaBoost/5. Comparison to Stacking.srt 4KB
  78. 3. Bootstrap Estimates and Bagging/2. Bootstrap Demo.srt 4KB
  79. 2. Bias-Variance Trade-Off/2. Bias-Variance Trade-Off.srt 4KB
  80. 6. Appendix FAQ/1. What is the Appendix.srt 4KB
  81. 2. Bias-Variance Trade-Off/3. Bias-Variance Decomposition.srt 4KB
  82. 1. Get Started/4. Plug-and-Play.srt 3KB
  83. 1. Get Started/2. Where to get the Code and Data.srt 3KB
  84. 5. AdaBoost/2. Additive Modeling.srt 2KB
  85. 0. Extras (Coupons & Freebies)/Readme.txt 962B
  86. 0. Websites You May Like/Readme.txt 962B
  87. Readme.txt 962B
  88. 0. Extras (Coupons & Freebies)/100 % OFF Lifetime Access Coupons.url 131B
  89. 0. Extras (Coupons & Freebies)/Free Udemy Coupons.url 131B
  90. 0. Websites You May Like/100 % OFF Lifetime Access Coupons.url 131B
  91. 0. Websites You May Like/Free Udemy Coupons.url 131B
  92. 0. Extras (Coupons & Freebies)/[GigaCourse.com].url 49B
  93. 0. Websites You May Like/[GigaCourse.com].url 49B
  94. [GigaCourse.com].url 49B