Summary
Ray and MLflow, two open source projects, combine to add scaling and experiment management to an ML platform. The talk introduces Ray Tune for distributed hyperparameter tuning and Ray Serve for scalable model serving, shows MLflow integrations for tracking and deployment, and demos a platform built on these tools.
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