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[] Udemy - Hyperparameter Optimization for Machine Learning

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  • 文件大小:3GB
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文件列表

  1. 06 Bayesian Optimization/006 Sequential Model-Based Optimization.mp4 114MB
  2. 08 Scikit-Optimize/014 Optimizing parameters of a CNN.mp4 111MB
  3. 06 Bayesian Optimization/017 Scikit-Optimize - Neuronal Networks.mp4 111MB
  4. 07 Other SMBO Algorithms/002 SMAC Demo.mp4 100MB
  5. 06 Bayesian Optimization/013 Scikit-Optimize - 1-Dimension.mp4 97MB
  6. 06 Bayesian Optimization/008 Multivariate Gaussian Distribution.mp4 84MB
  7. 06 Bayesian Optimization/011 Acquisition Functions.mp4 82MB
  8. 05 Basic Search Algorithms/009 Random Search with Hyperopt.mp4 81MB
  9. 04 Cross-Validation/003 Cross-Validation Schemes.mp4 80MB
  10. 06 Bayesian Optimization/009 Gaussian Process.mp4 76MB
  11. 06 Bayesian Optimization/005 Bayes Rule.mp4 68MB
  12. 04 Cross-Validation/004 Cross-Validation for model error estimation - Demo.mp4 66MB
  13. 03 Performance metrics/005 Creating your Own Metrics.mp4 64MB
  14. 02 Hyperparameter Tuning - Overview/001 Parameters and Hyperparameters.mp4 62MB
  15. 01 Introduction/001 Introduction.mp4 62MB
  16. 05 Basic Search Algorithms/004 Grid Search - Demo.mp4 59MB
  17. 04 Cross-Validation/001 Cross-Validation.mp4 58MB
  18. 04 Cross-Validation/005 Cross-Validation for Hyperparameter Tuning - Demo.mp4 57MB
  19. 04 Cross-Validation/009 Nested Cross-Validation - Demo.mp4 55MB
  20. 02 Hyperparameter Tuning - Overview/002 Hyperparameter Optimization.mp4 51MB
  21. 07 Other SMBO Algorithms/007 TPE with Hyperopt.mp4 50MB
  22. 04 Cross-Validation/008 Nested Cross-Validation.mp4 50MB
  23. 05 Basic Search Algorithms/008 Random Search with Scikit-Optimize.mp4 48MB
  24. 06 Bayesian Optimization/004 Joint and Conditional Probabilities.mp4 46MB
  25. 03 Performance metrics/004 Scikit-learn Metrics.mp4 46MB
  26. 05 Basic Search Algorithms/007 Random Search - Scikit-learn.mp4 44MB
  27. 06 Bayesian Optimization/003 Bayesian Inference - Introduction.mp4 43MB
  28. 04 Cross-Validation/007 Group Cross-Validation - Demo.mp4 43MB
  29. 05 Basic Search Algorithms/002 Manual Search.mp4 43MB
  30. 03 Performance metrics/002 Classification Metrics (Optional).mp4 43MB
  31. 07 Other SMBO Algorithms/004 TPE Procedure.mp4 42MB
  32. 05 Basic Search Algorithms/006 Random Search.mp4 41MB
  33. 04 Cross-Validation/006 Special Cross-Validation Schemes.mp4 41MB
  34. 08 Scikit-Optimize/006 Random search.mp4 38MB
  35. 08 Scikit-Optimize/015 Analyzing the CNN search.mp4 37MB
  36. 06 Bayesian Optimization/018 Scikit-Optimize - CNN - Search Analysis.mp4 37MB
  37. 06 Bayesian Optimization/014 Scikit-Optimize - Manual Search.mp4 36MB
  38. 08 Scikit-Optimize/007 Bayesian search with Gaussian processes.mp4 35MB
  39. 01 Introduction/002 Course Curriculum.mp4 35MB
  40. 06 Bayesian Optimization/007 Gaussian Distribution.mp4 35MB
  41. 07 Other SMBO Algorithms/001 SMAC.mp4 33MB
  42. 06 Bayesian Optimization/015 Scikit-Optimize - Automatic Search.mp4 31MB
  43. 08 Scikit-Optimize/011 Bayesian search with Scikit-learn wrapper.mp4 31MB
  44. 06 Bayesian Optimization/001 Sequential Search.mp4 31MB
  45. 06 Bayesian Optimization/010 Kernels.mp4 30MB
  46. 08 Scikit-Optimize/010 Parallelizing a bayesian search.mp4 26MB
  47. 07 Other SMBO Algorithms/006 TPE - why tree-structured_.mp4 26MB
  48. 05 Basic Search Algorithms/001 Basic Search Algorithms - Introduction.mp4 25MB
  49. 08 Scikit-Optimize/012 Changing the kernel of a Gaussian Process.mp4 25MB
  50. 06 Bayesian Optimization/016 Scikit-Optimize - Alternative Kernel.mp4 25MB
  51. 08 Scikit-Optimize/001 Scikit-Optimize.mp4 25MB
  52. 08 Scikit-Optimize/003 Hyperparameter Distributions.mp4 24MB
  53. 07 Other SMBO Algorithms/005 TPE hyperparameters.mp4 23MB
  54. 08 Scikit-Optimize/009 Bayes search with GBMs.mp4 23MB
  55. 08 Scikit-Optimize/008 Bayes search with Random Forests.mp4 23MB
  56. 06 Bayesian Optimization/002 Bayesian Optimization.mp4 22MB
  57. 07 Other SMBO Algorithms/003 Tree-structured Parzen Estimators - TPE.mp4 19MB
  58. 05 Basic Search Algorithms/005 Grid Search with different hyperparameter spaces.mp4 18MB
  59. 03 Performance metrics/006 Using Scikit-learn Metrics.mp4 18MB
  60. 08 Scikit-Optimize/004 Defining the hyperparameter space.mp4 17MB
  61. 03 Performance metrics/003 Regression Metrics (Optional).mp4 17MB
  62. 05 Basic Search Algorithms/003 Grid Search.mp4 16MB
  63. 01 Introduction/003 Course aim and knowledge requirements.mp4 16MB
  64. 08 Scikit-Optimize/002 Section Content.mp4 12MB
  65. 08 Scikit-Optimize/005 Defining the objective function.mp4 11MB
  66. 01 Introduction/004 Course Material.mp4 10MB
  67. 03 Performance metrics/001 Introduction.mp4 6MB
  68. 06 Bayesian Optimization/006 Sequential Model-Based Optimization.en.srt 20KB
  69. 06 Bayesian Optimization/008 Multivariate Gaussian Distribution.en.srt 19KB
  70. 06 Bayesian Optimization/013 Scikit-Optimize - 1-Dimension.en.srt 19KB
  71. 06 Bayesian Optimization/017 Scikit-Optimize - Neuronal Networks.en.srt 18KB
  72. 08 Scikit-Optimize/014 Optimizing parameters of a CNN.en.srt 18KB
  73. 04 Cross-Validation/003 Cross-Validation Schemes.en.srt 17KB
  74. 06 Bayesian Optimization/009 Gaussian Process.en.srt 16KB
  75. 06 Bayesian Optimization/011 Acquisition Functions.en.srt 16KB
  76. 06 Bayesian Optimization/005 Bayes Rule.en.srt 14KB
  77. 07 Other SMBO Algorithms/002 SMAC Demo.en.srt 14KB
  78. 02 Hyperparameter Tuning - Overview/001 Parameters and Hyperparameters.en.srt 14KB
  79. 05 Basic Search Algorithms/009 Random Search with Hyperopt.en.srt 13KB
  80. 04 Cross-Validation/001 Cross-Validation.en.srt 11KB
  81. 03 Performance metrics/005 Creating your Own Metrics.en.srt 11KB
  82. 02 Hyperparameter Tuning - Overview/002 Hyperparameter Optimization.en.srt 11KB
  83. 04 Cross-Validation/004 Cross-Validation for model error estimation - Demo.en.srt 11KB
  84. 05 Basic Search Algorithms/004 Grid Search - Demo.en.srt 10KB
  85. 04 Cross-Validation/005 Cross-Validation for Hyperparameter Tuning - Demo.en.srt 10KB
  86. 05 Basic Search Algorithms/008 Random Search with Scikit-Optimize.en.srt 10KB
  87. 03 Performance metrics/002 Classification Metrics (Optional).en.srt 10KB
  88. 05 Basic Search Algorithms/006 Random Search.en.srt 10KB
  89. 07 Other SMBO Algorithms/004 TPE Procedure.en.srt 9KB
  90. 06 Bayesian Optimization/003 Bayesian Inference - Introduction.en.srt 9KB
  91. 05 Basic Search Algorithms/002 Manual Search.en.srt 9KB
  92. 06 Bayesian Optimization/004 Joint and Conditional Probabilities.en.srt 9KB
  93. 04 Cross-Validation/008 Nested Cross-Validation.en.srt 9KB
  94. 06 Bayesian Optimization/007 Gaussian Distribution.en.srt 9KB
  95. 04 Cross-Validation/006 Special Cross-Validation Schemes.en.srt 9KB
  96. 04 Cross-Validation/009 Nested Cross-Validation - Demo.en.srt 9KB
  97. 03 Performance metrics/004 Scikit-learn Metrics.en.srt 8KB
  98. 06 Bayesian Optimization/018 Scikit-Optimize - CNN - Search Analysis.en.srt 8KB
  99. 08 Scikit-Optimize/015 Analyzing the CNN search.en.srt 8KB
  100. 01 Introduction/002 Course Curriculum.en.srt 8KB
  101. 06 Bayesian Optimization/010 Kernels.en.srt 8KB
  102. 07 Other SMBO Algorithms/007 TPE with Hyperopt.en.srt 8KB
  103. 07 Other SMBO Algorithms/001 SMAC.en.srt 7KB
  104. 06 Bayesian Optimization/014 Scikit-Optimize - Manual Search.en.srt 7KB
  105. 06 Bayesian Optimization/001 Sequential Search.en.srt 7KB
  106. 08 Scikit-Optimize/001 Scikit-Optimize.en.srt 7KB
  107. 05 Basic Search Algorithms/007 Random Search - Scikit-learn.en.srt 7KB
  108. 08 Scikit-Optimize/007 Bayesian search with Gaussian processes.en.srt 7KB
  109. 05 Basic Search Algorithms/001 Basic Search Algorithms - Introduction.en.srt 7KB
  110. 08 Scikit-Optimize/006 Random search.en.srt 6KB
  111. 04 Cross-Validation/007 Group Cross-Validation - Demo.en.srt 6KB
  112. 06 Bayesian Optimization/002 Bayesian Optimization.en.srt 6KB
  113. 06 Bayesian Optimization/015 Scikit-Optimize - Automatic Search.en.srt 5KB
  114. 08 Scikit-Optimize/011 Bayesian search with Scikit-learn wrapper.en.srt 5KB
  115. 07 Other SMBO Algorithms/005 TPE hyperparameters.en.srt 5KB
  116. 08 Scikit-Optimize/003 Hyperparameter Distributions.en.srt 5KB
  117. 07 Other SMBO Algorithms/006 TPE - why tree-structured_.en.srt 5KB
  118. 06 Bayesian Optimization/016 Scikit-Optimize - Alternative Kernel.en.srt 5KB
  119. 08 Scikit-Optimize/012 Changing the kernel of a Gaussian Process.en.srt 5KB
  120. 05 Basic Search Algorithms/003 Grid Search.en.srt 4KB
  121. 01 Introduction/001 Introduction.en.srt 4KB
  122. 07 Other SMBO Algorithms/003 Tree-structured Parzen Estimators - TPE.en.srt 4KB
  123. 03 Performance metrics/003 Regression Metrics (Optional).en.srt 4KB
  124. 01 Introduction/009 FAQ.html 4KB
  125. 08 Scikit-Optimize/008 Bayes search with Random Forests.en.srt 4KB
  126. 08 Scikit-Optimize/009 Bayes search with GBMs.en.srt 4KB
  127. 08 Scikit-Optimize/010 Parallelizing a bayesian search.en.srt 3KB
  128. 08 Scikit-Optimize/004 Defining the hyperparameter space.en.srt 3KB
  129. 01 Introduction/003 Course aim and knowledge requirements.en.srt 3KB
  130. 05 Basic Search Algorithms/005 Grid Search with different hyperparameter spaces.en.srt 3KB
  131. 08 Scikit-Optimize/002 Section Content.en.srt 3KB
  132. 08 Scikit-Optimize/005 Defining the objective function.en.srt 3KB
  133. 03 Performance metrics/006 Using Scikit-learn Metrics.en.srt 2KB
  134. 01 Introduction/004 Course Material.en.srt 2KB
  135. 06 Bayesian Optimization/012 Additional Reading Resources.html 2KB
  136. 01 Introduction/005 Jupyter notebooks.html 2KB
  137. 01 Introduction/008 Set up your computer - required packages.html 2KB
  138. 09 Moving Forward/001 What's next_.html 2KB
  139. 03 Performance metrics/001 Introduction.en.srt 1KB
  140. 01 Introduction/007 Datasets.html 1KB
  141. 08 Scikit-Optimize/013 Optimizing xgboost.html 1KB
  142. 01 Introduction/006 Presentations.html 1KB
  143. 04 Cross-Validation/002 Bias vs Variance (Optional).html 1KB
  144. 0. Websites you may like/[FCS Forum].url 133B
  145. 0. Websites you may like/[FreeCourseSite.com].url 127B
  146. 0. Websites you may like/[CourseClub.ME].url 122B