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

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

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收录时间：2022-01-24
最近下载：2024-11-12

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文件列表

  • 4.Deploying Machine Learning Models in Production/03_week-3-model-management-and-delivery/02_mlops-methodology/02_mlops-levels-1-2.mp4 28.1 MB
  • 1.Introduction to Machine Learning in Production/01_week-1-overview-of-the-ml-lifecycle-and-deployment/03_deployment/01_key-challenges.mp4 26.9 MB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/02_label-and-organize-data/01_obtaining-data.mp4 21.7 MB
  • 3.Machine Learning Modeling Pipelines in Production/02_week-2-model-resource-management-techniques/02_quantization-and-pruning/06_pruning.mp4 21.4 MB
  • 1.Introduction to Machine Learning in Production/01_week-1-overview-of-the-ml-lifecycle-and-deployment/03_deployment/04_monitoring.mp4 19.1 MB
  • 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/05_adding-features.mp4 19.0 MB
  • 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/03_data-augmentation.mp4 16.8 MB
  • 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/01_model-analysis-overview/01_model-performance-analysis.mp4 16.5 MB
  • 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/03_gdpr-and-privacy/06_right-to-be-forgotten.mp4 15.8 MB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/02_interpretability/02_intrinsically-interpretable-models.mp4 15.5 MB
  • 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/04_can-adding-data-hurt.mp4 15.3 MB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/02_scoping-process.mp4 14.1 MB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/04_diligence-on-value.mp4 13.8 MB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/02_interpretability/01_model-interpretation-methods.mp4 13.6 MB
  • 2.Machine Learning Data Lifecycle in Production/01_week-1-collecting-labeling-and-validating-data/03_collecting-data/01_importance-of-data.mp4 13.2 MB
  • 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/06_automl-on-the-cloud.mp4 12.4 MB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/01_explainable-ai/01_explainable-ai.mp4 12.2 MB
  • 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/03_enterprise-data-storage/01_feature-stores.mp4 11.5 MB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/02_label-and-organize-data/02_data-pipeline.mp4 11.2 MB
  • 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 11.1 MB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/03_understanding-model-predictions/11_ai-explanations.mp4 10.9 MB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/03_understanding-model-predictions/05_shapley-values.mp4 10.7 MB
  • 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 9.9 MB
  • 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 9.4 MB
  • 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/06_experiment-tracking.mp4 9.3 MB
  • 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 9.3 MB
  • 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/02_model-decay/03_ways-to-mitigate-model-decay.mp4 9.0 MB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/01_what-is-scoping.mp4 8.5 MB
  • 4.Deploying Machine Learning Models in Production/03_week-3-model-management-and-delivery/02_mlops-methodology/01_mlops-level-0.mp4 8.3 MB
  • 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/01_intro-to-automl.mp4 8.3 MB
  • 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/01_data-centric-ai-development.mp4 7.9 MB
  • 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/03_gdpr-and-privacy/01_responsible-ai.mp4 7.8 MB
  • 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/03_search-strategies.mp4 7.1 MB
  • 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/02_advanced-model-analysis-and-debugging/10_model-remediation.mp4 6.5 MB
  • 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/02_evolving-data/01_schema-development.mp4 6.4 MB
  • 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/03_enterprise-data-storage/02_data-warehouse.mp4 6.2 MB
  • 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/02_advanced-model-analysis-and-debugging/02_tfma-in-practice.mp4 5.8 MB
  • 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/05_measuring-automl-efficacy.mp4 5.6 MB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/04_course-resources/01_references_1706.06969.pdf 5.6 MB
  • 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/02_advanced-model-analysis-and-debugging/11_fairness.mp4 5.5 MB
  • 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/02_evolving-data/02_schema-environments.mp4 5.3 MB
  • 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/02_model-decay/01_what-is-model-decay.mp4 5.3 MB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/05_milestones-and-resourcing.mp4 5.0 MB
  • 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/03_enterprise-data-storage/03_data-lakes.mp4 5.0 MB
  • 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/02_model-decay/02_model-decay-detection.mp4 4.0 MB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/01_explainable-ai/02_explainable-ai_1910.10045.pdf 3.8 MB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/02_interpretability/03_interpretability_15-243.pdf 3.4 MB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_15-243.pdf 3.4 MB
  • 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/08_assignment-setup.mp4 3.4 MB
  • 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/02_advanced-model-analysis-and-debugging/09_residual-analysis.mp4 3.2 MB
  • 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/02_understanding-search-spaces.mp4 2.8 MB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/03_understanding-model-predictions/09_lime.mp4 2.2 MB
  • 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/02_advanced-model-analysis-and-debugging/05_benchmark-models.mp4 1.6 MB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_parsons.pdf 515.5 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_gpipe.py 355.9 kB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/04_course-resources/01_references_2004.07213v2 49.3 kB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/04_course-resources/01_references_2010.02013 45.2 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_2010.02013 43.6 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1811.06965 41.9 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1511.04508 41.4 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1911.04252 40.8 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1803.03635 40.7 kB
  • 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 40.4 kB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/04_course-resources/01_references_1912.02292 40.4 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1801.01489 40.4 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1910.08381 39.8 kB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/04_course-resources/01_references_2011.09926 39.5 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1712.05877 39.5 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1806.03377 39.3 kB
  • 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/04_neural-architecture-search_1603.01670 39.0 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1603.01670 39.0 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_1409.4842 38.8 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/04_course-resources/01_course-3-optional-references_2011.09926 37.9 kB
  • 1.Introduction to Machine Learning in Production/01_week-1-overview-of-the-ml-lifecycle-and-deployment/03_deployment/01_key-challenges.en.srt 23.5 kB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/02_label-and-organize-data/01_obtaining-data.en.srt 19.1 kB
  • 1.Introduction to Machine Learning in Production/01_week-1-overview-of-the-ml-lifecycle-and-deployment/03_deployment/04_monitoring.en.srt 17.6 kB
  • 4.Deploying Machine Learning Models in Production/03_week-3-model-management-and-delivery/02_mlops-methodology/02_mlops-levels-1-2.en.srt 16.9 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/02_interpretability/01_model-interpretation-methods.en.srt 15.1 kB
  • 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/03_data-augmentation.en.srt 14.4 kB
  • 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/06_automl-on-the-cloud.en.srt 13.2 kB
  • 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 12.8 kB
  • 1.Introduction to Machine Learning in Production/01_week-1-overview-of-the-ml-lifecycle-and-deployment/03_deployment/01_key-challenges.en.txt 12.3 kB
  • 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/01_model-analysis-overview/01_model-performance-analysis.en.srt 12.2 kB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/04_course-resources/01_references_DLDL.html 12.1 kB
  • 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/05_adding-features.en.srt 11.6 kB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/04_diligence-on-value.en.srt 11.3 kB
  • 4.Deploying Machine Learning Models in Production/03_week-3-model-management-and-delivery/02_mlops-methodology/02_mlops-levels-1-2.en.txt 10.8 kB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/02_label-and-organize-data/01_obtaining-data.en.txt 10.2 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/01_explainable-ai/01_explainable-ai.en.srt 10.0 kB
  • 1.Introduction to Machine Learning in Production/01_week-1-overview-of-the-ml-lifecycle-and-deployment/03_deployment/04_monitoring.en.txt 9.4 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/03_understanding-model-predictions/05_shapley-values.en.srt 9.2 kB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/02_scoping-process.en.srt 9.1 kB
  • 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 9.1 kB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/02_label-and-organize-data/02_data-pipeline.en.srt 8.8 kB
  • 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/03_enterprise-data-storage/01_feature-stores.en.srt 8.7 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/03_understanding-model-predictions/11_ai-explanations.en.srt 8.7 kB
  • 4.Deploying Machine Learning Models in Production/03_week-3-model-management-and-delivery/02_mlops-methodology/01_mlops-level-0.en.srt 8.5 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/02_interpretability/01_model-interpretation-methods.en.txt 8.1 kB
  • 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/09_automl_quiz.html 7.7 kB
  • 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/06_experiment-tracking.en.srt 7.6 kB
  • 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/03_data-augmentation.en.txt 7.5 kB
  • 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/05_adding-features.en.txt 7.5 kB
  • 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 7.4 kB
  • 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/01_intro-to-automl.en.srt 7.4 kB
  • 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/02_evolving-data/01_schema-development.en.srt 7.3 kB
  • 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/02_advanced-model-analysis-and-debugging/11_fairness.en.srt 7.2 kB
  • 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/06_automl-on-the-cloud.en.txt 7.0 kB
  • 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 6.8 kB
  • 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 6.8 kB
  • 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/04_graded-assessment/01_modeling-challenges_exam.html 6.5 kB
  • 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/03_gdpr-and-privacy/01_responsible-ai.en.srt 6.3 kB
  • 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/01_model-analysis-overview/01_model-performance-analysis.en.txt 6.3 kB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/07_scoping-optional_quiz.html 6.3 kB
  • 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/02_evolving-data/02_schema-environments.en.srt 6.2 kB
  • 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/03_search-strategies.en.srt 6.1 kB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/04_diligence-on-value.en.txt 5.9 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/03_understanding-model-predictions/05_shapley-values.en.txt 5.9 kB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/03_scoping-optional/02_scoping-process.en.txt 5.9 kB
  • 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/03_enterprise-data-storage/02_data-warehouse.en.srt 5.6 kB
  • 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/02_model-decay/01_what-is-model-decay.en.srt 5.4 kB
  • 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/03_enterprise-data-storage/01_feature-stores.en.txt 5.4 kB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/04_course-resources/01_references_instructions.html 5.3 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/01_explainable-ai/01_explainable-ai.en.txt 5.2 kB
  • 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/05_measuring-automl-efficacy.en.srt 4.9 kB
  • 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 4.8 kB
  • 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 4.7 kB
  • 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/01_intro-to-automl.en.txt 4.7 kB
  • 1.Introduction to Machine Learning in Production/03_week-3-data-definition-and-baseline/02_label-and-organize-data/02_data-pipeline.en.txt 4.7 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/03_understanding-model-predictions/11_ai-explanations.en.txt 4.6 kB
  • 4.Deploying Machine Learning Models in Production/03_week-3-model-management-and-delivery/02_mlops-methodology/01_mlops-level-0.en.txt 4.5 kB
  • 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 4.5 kB
  • 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 4.4 kB
  • 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/03_gdpr-and-privacy/07_gdpr-and-privacy_quiz.html 4.3 kB
  • 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 4.1 kB
  • 3.Machine Learning Modeling Pipelines in Production/05_week-5-interpretability/05_acknowledgments/01_acknowledgements_instructions.html 4.1 kB
  • 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/03_gdpr-and-privacy/01_responsible-ai.en.txt 4.1 kB
  • 1.Introduction to Machine Learning in Production/02_week-2-select-and-train-a-model/03_data-iteration/06_experiment-tracking.en.txt 4.0 kB
  • 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/02_model-decay/05_model-decay_quiz.html 4.0 kB
  • 4.Deploying Machine Learning Models in Production/04_week-4-model-monitoring-and-logging/02_model-decay/02_model-decay-detection.en.srt 4.0 kB
  • 3.Machine Learning Modeling Pipelines in Production/01_week-1-neural-architecture-search/03_automl/03_search-strategies.en.txt 3.9 kB
  • 3.Machine Learning Modeling Pipelines in Production/04_week-4-model-analysis/02_advanced-model-analysis-and-debugging/11_fairness.en.txt 3.8 kB
  • 2.Machine Learning Data Lifecycle in Production/03_week-3-data-journey-and-data-storage/02_evolving-data/01_schema-development.en.txt 3.8 kB
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