3Deploy and Retrain a Model

• 3.1Registering and Deploying Models (Endpoints)

  Understand registering trained models (model registry) and deploying them to inference endpoints—real-time online endpoints and batch endpoints. Put models into production.

• 3.2Monitoring, Retraining, and MLOps

  Understand post-deployment monitoring (data drift, performance, inference logs), automating retraining, and MLOps (pipelines, CI/CD, model versioning). Keep models healthy over time.