Summary and Quiz
Explore how to maintain production ML systems with continuous monitoring using SageMaker Model Monitor. Understand setting up drift detection, configuring alerts with CloudWatch and EventBridge, automating retraining pipelines, and applying bias detection tools like SageMaker Clarify and LLM evaluation. Gain practical knowledge to ensure model fairness and reliability.
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Summary
This chapter explained how to operate production ML systems with continuous observability and automated remediation. It covered configuring SageMaker Model Monitor to detect data and concept drift, building CloudWatch alarms for alerting, wiring events through EventBridge and Lambda for automated retraining, and using SageMaker Clarify and LLM evaluation to monitor bias and safety. ...