Definition
The systematic and rigorous processes used to verify that a machine learning model functions correctly, meets performance metrics, and is reliable before and after deployment.
In short: The systematic and rigorous processes used to verify that a machine learning model functions correctly, meets performance metrics, and is reliable before and after deployment.