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Production ML Architecture
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Classroom Contents
Infusing Trusted AI Using Machine Learning Payload Logging on Kubernetes
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- 1 Intro
- 2 Production Model Serving? How hard could it be?
- 3 KNative
- 4 KF Serving: Default and Canary Configurations
- 5 Supported Frameworks, Components and Storage Subsystems
- 6 Inference Service Control Plane
- 7 KFServing Deployment View
- 8 KF Serving Examples
- 9 Model Serving is accomplished. Can the predictions be trusted?
- 10 Production ML Architecture
- 11 Payload Logging Architecture Examples
- 12 Linux Foundation Al & Data
- 13 Trusted Al Lifecycle through Open Source
- 14 Al needs to explain its decisions!
- 15 Bias in Al: Criminal Justice System
- 16 Adversarial Robustness
- 17 Al Explainability 360
- 18 Al Fairness 360
- 19 LFAI Trusted Al Projects with Kubeflow Serving
- 20 Demo Flow
