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[] Coursera – Machine Learning Engineering for Production (MLOps) Specialization

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  • 文件大小:513MB
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文件列表

  1. 4.Deploying Machine Learning Models in Production/03_week-3-model-management-and-delivery/02_mlops-methodology/02_mlops-levels-1-2.mp4 27MB
  2. 1.Introduction to Machine Learning in Production/01_week-1-overview-of-the-ml-lifecycle-and-deployment/03_deployment/01_key-challenges.mp4 26MB
  3. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/02_label-and-organize-data/01_obtaining-data.mp4 21MB
  4. 3.Machine Learning Modeling Pipelines in Production/02_week-2-model-resource-management-techniques/02_quantization-and-pruning/06_pruning.mp4 20MB
  5. 1.Introduction to Machine Learning in Production/01_week-1-overview-of-the-ml-lifecycle-and-deployment/03_deployment/04_monitoring.mp4 18MB
  6. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/05_adding-features.mp4 18MB
  7. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/03_data-augmentation.mp4 16MB
  8. 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/01_model-analysis-overview/01_model-performance-analysis.mp4 16MB
  9. 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/03_gdpr-and-privacy/06_right-to-be-forgotten.mp4 15MB
  10. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/02_interpretability/02_intrinsically-interpretable-models.mp4 15MB
  11. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/04_can-adding-data-hurt.mp4 15MB
  12. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/02_scoping-process.mp4 13MB
  13. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/04_diligence-on-value.mp4 13MB
  14. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/02_interpretability/01_model-interpretation-methods.mp4 13MB
  15. 2.Machine Learning Data Lifecycle in Production/01_week-1-collecting-labeling-and-validating-data/03_collecting-data/01_importance-of-data.mp4 13MB
  16. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/06_automl-on-the-cloud.mp4 12MB
  17. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/01_explainable-ai/01_explainable-ai.mp4 12MB
  18. 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/03_enterprise-data-storage/01_feature-stores.mp4 11MB
  19. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/02_label-and-organize-data/02_data-pipeline.mp4 11MB
  20. 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/01_data-journey-and-data-storage/01_data-journey.mp4 11MB
  21. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/03_understanding-model-predictions/11_ai-explanations.mp4 10MB
  22. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/03_understanding-model-predictions/05_shapley-values.mp4 10MB
  23. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/01_selecting-and-training-a-model/01_modeling-overview.mp4 9MB
  24. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/01_selecting-and-training-a-model/02_key-challenges.mp4 9MB
  25. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/06_experiment-tracking.mp4 9MB
  26. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/07_from-big-data-to-good-data.mp4 9MB
  27. 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/02_model-decay/03_ways-to-mitigate-model-decay.mp4 9MB
  28. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/01_what-is-scoping.mp4 8MB
  29. 4.Deploying Machine Learning Models in Production/03_week-3-model-management-and-delivery/02_mlops-methodology/01_mlops-level-0.mp4 8MB
  30. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/01_intro-to-automl.mp4 8MB
  31. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/01_data-centric-ai-development.mp4 8MB
  32. 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/03_gdpr-and-privacy/01_responsible-ai.mp4 7MB
  33. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/03_search-strategies.mp4 7MB
  34. 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/02_advanced-model-analysis-and-debugging/10_model-remediation.mp4 6MB
  35. 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/02_evolving-data/01_schema-development.mp4 6MB
  36. 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/03_enterprise-data-storage/02_data-warehouse.mp4 6MB
  37. 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/02_advanced-model-analysis-and-debugging/02_tfma-in-practice.mp4 6MB
  38. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/05_measuring-automl-efficacy.mp4 5MB
  39. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/04_course-resources/01_references_1706.06969.pdf 5MB
  40. 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/02_advanced-model-analysis-and-debugging/11_fairness.mp4 5MB
  41. 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/02_evolving-data/02_schema-environments.mp4 5MB
  42. 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/02_model-decay/01_what-is-model-decay.mp4 5MB
  43. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/05_milestones-and-resourcing.mp4 5MB
  44. 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/03_enterprise-data-storage/03_data-lakes.mp4 5MB
  45. 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/02_model-decay/02_model-decay-detection.mp4 4MB
  46. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/01_explainable-ai/02_explainable-ai_1910.10045.pdf 4MB
  47. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/02_interpretability/03_interpretability_15-243.pdf 3MB
  48. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_15-243.pdf 3MB
  49. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/08_assignment-setup.mp4 3MB
  50. 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/02_advanced-model-analysis-and-debugging/09_residual-analysis.mp4 3MB
  51. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/02_understanding-search-spaces.mp4 3MB
  52. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/03_understanding-model-predictions/09_lime.mp4 2MB
  53. 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/02_advanced-model-analysis-and-debugging/05_benchmark-models.mp4 2MB
  54. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_parsons.pdf 503KB
  55. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_gpipe.py 348KB
  56. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/04_course-resources/01_references_2004.07213v2 48KB
  57. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/04_course-resources/01_references_2010.02013 44KB
  58. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_2010.02013 43KB
  59. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1811.06965 41KB
  60. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1511.04508 40KB
  61. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1911.04252 40KB
  62. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1803.03635 40KB
  63. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/08_week-2-optional-references_1912.02292 39KB
  64. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/04_course-resources/01_references_1912.02292 39KB
  65. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1801.01489 39KB
  66. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1910.08381 39KB
  67. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/04_course-resources/01_references_2011.09926 39KB
  68. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1712.05877 39KB
  69. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1806.03377 38KB
  70. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/04_neural-architecture-search_1603.01670 38KB
  71. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1603.01670 38KB
  72. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1409.4842 38KB
  73. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_2011.09926 37KB
  74. 1.Introduction to Machine Learning in Production/01_week-1-overview-of-the-ml-lifecycle-and-deployment/03_deployment/01_key-challenges.en.srt 23KB
  75. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/02_label-and-organize-data/01_obtaining-data.en.srt 19KB
  76. 1.Introduction to Machine Learning in Production/01_week-1-overview-of-the-ml-lifecycle-and-deployment/03_deployment/04_monitoring.en.srt 17KB
  77. 4.Deploying Machine Learning Models in Production/03_week-3-model-management-and-delivery/02_mlops-methodology/02_mlops-levels-1-2.en.srt 16KB
  78. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/02_interpretability/01_model-interpretation-methods.en.srt 15KB
  79. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/03_data-augmentation.en.srt 14KB
  80. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/06_automl-on-the-cloud.en.srt 13KB
  81. 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/03_gdpr-and-privacy/06_right-to-be-forgotten.en.srt 12KB
  82. 1.Introduction to Machine Learning in Production/01_week-1-overview-of-the-ml-lifecycle-and-deployment/03_deployment/01_key-challenges.en.txt 12KB
  83. 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/01_model-analysis-overview/01_model-performance-analysis.en.srt 12KB
  84. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/04_course-resources/01_references_DLDL.html 12KB
  85. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/05_adding-features.en.srt 11KB
  86. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/04_diligence-on-value.en.srt 11KB
  87. 4.Deploying Machine Learning Models in Production/03_week-3-model-management-and-delivery/02_mlops-methodology/02_mlops-levels-1-2.en.txt 11KB
  88. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/02_label-and-organize-data/01_obtaining-data.en.txt 10KB
  89. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/01_explainable-ai/01_explainable-ai.en.srt 10KB
  90. 1.Introduction to Machine Learning in Production/01_week-1-overview-of-the-ml-lifecycle-and-deployment/03_deployment/04_monitoring.en.txt 9KB
  91. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/03_understanding-model-predictions/05_shapley-values.en.srt 9KB
  92. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/02_scoping-process.en.srt 9KB
  93. 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/02_model-decay/03_ways-to-mitigate-model-decay.en.srt 9KB
  94. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/02_label-and-organize-data/02_data-pipeline.en.srt 9KB
  95. 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/03_enterprise-data-storage/01_feature-stores.en.srt 9KB
  96. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/03_understanding-model-predictions/11_ai-explanations.en.srt 8KB
  97. 4.Deploying Machine Learning Models in Production/03_week-3-model-management-and-delivery/02_mlops-methodology/01_mlops-level-0.en.srt 8KB
  98. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/02_interpretability/01_model-interpretation-methods.en.txt 8KB
  99. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/09_automl_quiz.html 8KB
  100. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/06_experiment-tracking.en.srt 7KB
  101. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/03_data-augmentation.en.txt 7KB
  102. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/05_adding-features.en.txt 7KB
  103. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/04_can-adding-data-hurt.en.srt 7KB
  104. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/01_intro-to-automl.en.srt 7KB
  105. 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/02_evolving-data/01_schema-development.en.srt 7KB
  106. 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/02_advanced-model-analysis-and-debugging/11_fairness.en.srt 7KB
  107. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/06_automl-on-the-cloud.en.txt 7KB
  108. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/01_selecting-and-training-a-model/02_key-challenges.en.srt 7KB
  109. 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/03_gdpr-and-privacy/06_right-to-be-forgotten.en.txt 7KB
  110. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/04_graded-assessment/01_modeling-challenges_exam.html 6KB
  111. 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/03_gdpr-and-privacy/01_responsible-ai.en.srt 6KB
  112. 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/01_model-analysis-overview/01_model-performance-analysis.en.txt 6KB
  113. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/07_scoping-optional_quiz.html 6KB
  114. 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/02_evolving-data/02_schema-environments.en.srt 6KB
  115. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/03_search-strategies.en.srt 6KB
  116. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/04_diligence-on-value.en.txt 6KB
  117. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/03_understanding-model-predictions/05_shapley-values.en.txt 6KB
  118. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/02_scoping-process.en.txt 6KB
  119. 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/03_enterprise-data-storage/02_data-warehouse.en.srt 5KB
  120. 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/02_model-decay/01_what-is-model-decay.en.srt 5KB
  121. 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/03_enterprise-data-storage/01_feature-stores.en.txt 5KB
  122. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/04_course-resources/01_references_instructions.html 5KB
  123. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/01_explainable-ai/01_explainable-ai.en.txt 5KB
  124. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/05_measuring-automl-efficacy.en.srt 5KB
  125. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/04_can-adding-data-hurt.en.txt 5KB
  126. 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/02_model-decay/03_ways-to-mitigate-model-decay.en.txt 5KB
  127. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/01_intro-to-automl.en.txt 5KB
  128. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/02_label-and-organize-data/02_data-pipeline.en.txt 5KB
  129. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/03_understanding-model-predictions/11_ai-explanations.en.txt 5KB
  130. 4.Deploying Machine Learning Models in Production/03_week-3-model-management-and-delivery/02_mlops-methodology/01_mlops-level-0.en.txt 4KB
  131. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/01_selecting-and-training-a-model/02_key-challenges.en.txt 4KB
  132. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/07_from-big-data-to-good-data.en.srt 4KB
  133. 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/03_gdpr-and-privacy/07_gdpr-and-privacy_quiz.html 4KB
  134. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/01_data-centric-ai-development.en.srt 4KB
  135. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/05_acknowledgments/01_acknowledgements_instructions.html 4KB
  136. 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/03_gdpr-and-privacy/01_responsible-ai.en.txt 4KB
  137. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/06_experiment-tracking.en.txt 4KB
  138. 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/02_model-decay/05_model-decay_quiz.html 4KB
  139. 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/02_model-decay/02_model-decay-detection.en.srt 4KB
  140. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/03_search-strategies.en.txt 4KB
  141. 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/02_advanced-model-analysis-and-debugging/11_fairness.en.txt 4KB
  142. 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/02_evolving-data/01_schema-development.en.txt 4KB
  143. 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/03_enterprise-data-storage/03_data-lakes.en.srt 4KB
  144. 4.Deploying Machine Learning Models in Production/03_week-3-model-management-and-delivery/02_mlops-methodology/07_mlops-methodology_quiz.html 4KB
  145. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/01_what-is-scoping.en.srt 3KB
  146. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/01_explainable-ai/03_explainable-ai_quiz.html 3KB
  147. 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/02_evolving-data/02_schema-environments.en.txt 3KB
  148. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/05_measuring-automl-efficacy.en.txt 3KB
  149. 2.Machine Learning Data Lifecycle in Production/01_week-1-collecting-labeling-and-validating-data/04_labeling-data/04_data-labeling_quiz.html 3KB
  150. 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/03_enterprise-data-storage/02_data-warehouse.en.txt 3KB
  151. 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/02_model-decay/01_what-is-model-decay.en.txt 3KB
  152. 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/02_evolving-data/03_schema-environments_quiz.html 3KB
  153. 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/07_from-big-data-to-good-data.en.txt 3KB
  154. 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/01_model-analysis-overview/03_model-analysis_quiz.html 3KB
  155. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/08_assignment-setup.en.srt 3KB
  156. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/02_interpretability/04_interpretability_quiz.html 3KB
  157. 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/02_understanding-search-spaces.en.srt 2KB
  158. 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/03_understanding-model-predictions/09_lime.en.srt 2KB
  159. 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/01_what-is-scoping.en.txt 2KB
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