Model Drift Training Checkpoint

Rascunho de traducao automatica (Portuguese) for "Model Drift Training Checkpoint": Model Drift Training Checkpoint is a ml recovery artifact that saves model state during learning for changes in model performance over time. It uses weights, optimizer state, and run metadata so teams can resume or inspect training safely while keeping evidence, reliability, and public-safe operational boundaries clear.

“Exemplo em rascunho: The machine learning team used Model Drift Training Checkpoint when the live population changed, so the team could resume or inspect training safely before the model moved into evaluation.”