Overview
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This course shows how to build an MLSecOps workflow on Kubernetes using KServe, Knative, Apache Kafka, and Trusted AI tools. It covers serving models, persisting payloads, and automating real-time evaluations and offline analysis for explanations, fairness, and potential security threats.
Syllabus
Introduction
Power of Choice
Security in AI
Demo
ML Pipelines
ML Pipeline Metrics
CaseUp
Offline ML Evaluation
Online ML Evaluation
Case Service
Predictors
Fairness Detections
Loggers
Data ingestion
Demonstration
Trust AI
Istio
Taught by
Linux Foundation