Privacy in the ML Pipeline

Embed privacy into the ML pipeline end to end. Learn data-source clearance, feature-store privacy tags, training-data minimisation and provenance, model artefacts as personal data (memorisation risk), inference-time controls, and CI/CD privacy gates that block non-compliant releases.