CourseClub Me Coursera - Machine Learning Engineering for Production MLOps Specialization

1. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 01 - Specialization overview.mp439.95MB
2. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 02 - Welcome.mp420.35MB
3. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 03 - Steps of an ML Project.mp49.04MB
4. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 04 - Case study speech recognition.mp424.28MB
5. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 05 - Course outline.mp46.44MB
6. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 06 - Key challenges.mp425.62MB
7. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 07 - Deployment patterns.mp420.05MB
8. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 08 - Monitoring.mp418.25MB
9. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 09 - Pipeline monitoring.mp416.17MB
10. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 10 - Modeling overview.mp49.4MB
11. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 11 - Key challenges.mp48.98MB
12. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 12 - Why low average error isn't good enough.mp40B
13. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 13 - Establish a baseline.mp415.99MB
14. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 14 - Tips for getting started.mp411.07MB
15. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 15 - Error analysis example.mp413.74MB
16. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 16 - Prioritizing what to work on.mp410.23MB
17. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 17 - Skewed datastes.mp420.11MB
18. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 18 - Performance auditing.mp415.76MB
19. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 19 - Data-centric AI development.mp47.52MB
20. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 20 - A useful picture of data augmentation.mp40B
21. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 21 - Data augmentation.mp416.45MB
22. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 22 - Can adding data hurt.mp414.57MB
23. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 23 - Adding features.mp418.1MB
24. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 24 - Experiment tracking.mp48.86MB
25. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 25 - From big data to good data.mp48.85MB
26. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 26 - Why is data definition hard.mp410.06MB
27. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 27 - More label ambiguity examples.mp414.75MB
28. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 28 - Major types of data problems.mp420MB
29. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 29 - Small data and label consistency.mp415.3MB
30. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 30 - Improving label consistency.mp416.04MB
31. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 31 - Human level performance (HLP).mp418.51MB
32. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 32 - Raising HLP.mp421.81MB
33. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 33 - Obtaining data.mp420.71MB
34. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 34 - Data pipeline.mp410.66MB
35. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 35 - Meta-data, data provenance and lineage.mp40B
36. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 36 - Balanced train dev test splits.mp410.81MB
37. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 37 - What is scoping.mp48.11MB
38. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 38 - Scoping process.mp413.49MB
39. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 39 - Diligence on feasibility and value.mp423.23MB
40. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 40 - Diligence on value.mp413.19MB
41. 1. Introduction to Machine Learning in Production/introduction-to-machine-learning-in-production - 41 - Milestones and resourcing.mp44.78MB
42. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 01 - Specialization overview.mp439.95MB
43. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 02 - Course Overview.mp416.02MB
44. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 03 - Overview.mp418.03MB
45. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 04 - ML Pipelines.mp410.2MB
46. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 05 - Importance of Data.mp412.61MB
47. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 06 - Example Application Suggesting Runs.mp410.98MB
48. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 07 - Responsible Data Security, Privacy & Fairness.mp40B
49. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 08 - Case Study Degraded Model Performance.mp40B
50. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 09 - Data and Concept Change in Production ML.mp40B
51. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 10 - Process Feedback and Human Labeling.mp414.56MB
52. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 11 - Detecting Data Issues.mp412.44MB
53. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 12 - TensorFlow Data Validation.mp48.82MB
54. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 13 - Introduction to Preprocessing.mp410.05MB
55. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 14 - Preprocessing Operations.mp411.82MB
56. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 15 - Feature Engineering Techniques.mp420.32MB
57. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 16 - Feature Crosses.mp45.28MB
58. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 17 - Preprocessing Data at Scale.mp417.63MB
59. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 18 - TensorFlow Transform.mp417.53MB
60. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 19 - Hello World with tf.Transform.mp410.38MB
61. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 20 - Feature Spaces.mp46.32MB
62. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 21 - Feature Selection.mp45.71MB
63. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 22 - Filter Methods.mp48.01MB
64. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 23 - Wrapper Methods.mp47.26MB
65. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 24 - Embedded Methods.mp47.49MB
66. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 25 - Data Journey.mp410.6MB
67. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 26 - Introduction to ML Metadata.mp413.16MB
68. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 27 - ML Metadata in Action.mp46.19MB
69. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 28 - Schema Development.mp46.1MB
70. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 29 - Schema Environments.mp45.08MB
71. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 30 - Feature Stores.mp410.96MB
72. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 31 - Data Warehouse.mp45.92MB
73. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 32 - Data Lakes.mp44.75MB
74. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 33 - Semi-supervised Learning.mp46.49MB
75. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 34 - Active Learning.mp45.97MB
76. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 35 - Weak Supervision.mp46.95MB
77. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 36 - Data Augmentation.mp46.17MB
78. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 37 - Time Series.mp412.65MB
79. 2. Machine Learning Data Lifecycle in Production/machine-learning-data-lifecycle-in-production - 38 - Sensors and Signals.mp44.34MB
80. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 01 - Course Overview.mp410.47MB
81. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 02 - Hyperparameter Tuning.mp46.59MB
82. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 03 - Keras Autotuner Demo.mp49.08MB
83. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 04 - Intro to AutoML.mp47.9MB
84. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 05 - Understanding Search Spaces.mp42.68MB
85. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 06 - Search Strategies.mp46.78MB
86. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 07 - Measuring AutoML Efficacy.mp45.37MB
87. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 08 - AutoML on the Cloud.mp411.84MB
88. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 09 - Assignment Setup.mp43.22MB
89. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 10 - Dimensionality Effect on Performance.mp40B
90. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 11 - Curse of Dimensionality.mp413.83MB
91. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 12 - Curse of Dimensionality an Example.mp40B
92. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 13 - Manual Dimensionality Reduction.mp40B
93. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 15 - Algorithmic Dimensionality Reduction.mp40B
94. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 16 - Principal Components Analysis.mp40B
95. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 17 - Other Techniques.mp410.86MB
96. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 18 - Mobile, IoT, and Similar Use Cases.mp40B
97. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 19 - Benefits and Process of Quantization.mp40B
98. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 20 - Post Training Quantization.mp48.65MB
99. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 21 - Quantization Aware Training.mp46.26MB
100. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 22 - Pruning.mp420.42MB
101. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 23 - Distributed Training.mp415.94MB
102. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 24 - High-Performance Ingestion.mp415.77MB
103. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 26 - Teacher and Student Networks.mp44.35MB
104. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 27 - Knowledge Distillation Techniques.mp40B
105. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 29 - Model Performance Analysis.mp415.69MB
106. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 31 - TFMA in Practice.mp45.52MB
107. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 32 - Model Debugging Overview.mp44.72MB
108. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 33 - Benchmark Models.mp41.57MB
109. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 35 - Adversarial Attack Demo.mp411.36MB
110. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 36 - Residual Analysis.mp43.09MB
111. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 37 - Model Remediation.mp46.21MB
112. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 38 - Fairness.mp45.27MB
113. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 39 - Measuring Fairness.mp48.01MB
114. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 40 - Continuous Evaluation and Monitoring.mp40B
115. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 41 - Explainable AI.mp411.59MB
116. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 42 - Model Interpretation Methods.mp413.01MB
117. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 43 - Intrinsically Interpretable Models.mp40B
118. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 44 - Model Agnostic Methods.mp42.46MB
119. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 45 - Partial Dependence Plots.mp47.41MB
120. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 46 - Permutation Feature Importance.mp40B
121. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 47 - Shapley Values.mp410.21MB
122. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 48 - SHapley Additive exPlanations (SHAP).mp40B
123. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 49 - Testing Concept Activation Vectors.mp40B
124. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 50 - LIME.mp42.11MB
125. 3. Machine Learning Modeling Pipelines in Production/machine-learning-modeling-pipelines-in-production - 51 - AI Explanations.mp410.35MB