Results for "deployment"

A mismatch between training and deployment data distributions that can degrade model performance.

Systematic differences in model outcomes across groups; arises from data, labels, and deployment context.

Automated testing and deployment processes for models and data workflows, extending DevOps to ML artifacts.

Central system to store model versions, metadata, approvals, and deployment state.

Model behaves well during training but not deployment.

Review process before deployment.

Running new model alongside production without user impact.

Maintaining two environments for instant rollback.