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Intro
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Classroom Contents
Minimize Risk and Accelerate MLOps with ML Monitoring and Explainability
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- 1 Intro
- 2 Key Use Cases of ML In Finance
- 3 Models fail frequently
- 4 Most models are a black box
- 5 Regulations and Guidelines
- 6 MPM illuminates the black box
- 7 Catch Performance Issue with Labels
- 8 Catch Performance Issue with Drift
- 9 Catch Performance Issue with Data Errors
- 10 Catch Bias Issues
- 11 Solution - Explainability
- 12 Explaining a Prediction
- 13 Explanations - The Fed Remarks
- 14 Explaining a Segment or Model
- 15 Model Summary Report Powered by Explainability
- 16 Putting it together - Monitoring & Explainability
- 17 MPM Across the ML Lifecycle
- 18 Fiddler in Action: Top 5 Bank
