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Recap
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Classroom Contents
Testing ML Models in Production - Detecting Data and Concept Drift
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- 1 Intro
- 2 ML Cycle
- 3 Data Monitoring
- 4 KS Test
- 5 Categorical Features
- 6 Oneway Chisquared
- 7 Monitoring Tests
- 8 Tools
- 9 ML Flow
- 10 Notebooks
- 11 ML Workflow
- 12 ML Flow Delta
- 13 Other Notebooks
- 14 Widgets
- 15 Notebook Setup
- 16 Train Cycle Learn Pipeline
- 17 Data Logging
- 18 ML Flow Run
- 19 ML Flow Model Registry
- 20 ML Flow Experiment
- 21 Model Registry
- 22 New Data
- 23 Feature Checks
- 24 ML Flow Registry
- 25 Null Proportion
- 26 New Incoming Data
- 27 Chisquared Test
- 28 Action
- 29 Model Parameters
- 30 Model Staging
- 31 Model Migration
- 32 Missingness Check
- 33 Price Check
- 34 Categorical Check
- 35 Recap
