From the source

Govern models with MLflow and Amazon SageMaker AI Model Registry sync: Part 1

Amazon SageMaker AI Model Registry sync with MLflow now carries training metrics, evaluation results, lineage, and lifecycle stage promotion, enabling governance officers to validate and approve models from the registry without leaving the MLflow workflow.

From the source
That sync is now substantially richer. It carries training metrics, evaluation results, and lineage. It also adds lifecycle stage promotion driven from MLflow, so you can govern candidate models from a single system of record without needing data scientists to leave their experimentation workflow.
aws.amazon.com

Other stories

Other stories

Govern models with MLflow and Amazon SageMaker AI Model Registry sync: Part 1

From the source

Other stories