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MLSecOps - Automated Online and Offline ML Model Evaluations on Kubernetes

MLSecOps - Automated Online and Offline ML Model Evaluations on Kubernetes

Linux Foundation via YouTube Direct link

Introduction

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Introduction

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Classroom Contents

MLSecOps - Automated Online and Offline ML Model Evaluations on Kubernetes

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  1. 1 Introduction
  2. 2 Power of Choice
  3. 3 Security in AI
  4. 4 Demo
  5. 5 ML Pipelines
  6. 6 ML Pipeline Metrics
  7. 7 CaseUp
  8. 8 Offline ML Evaluation
  9. 9 Online ML Evaluation
  10. 10 Case Service
  11. 11 Predictors
  12. 12 Fairness Detections
  13. 13 Loggers
  14. 14 Data ingestion
  15. 15 Demonstration
  16. 16 Trust AI
  17. 17 Istio

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