Evaluation, Monitoring, and Model Degradation in Production AI Systems

Training metrics show model performance on static data, while production metrics reflect real, changing inputs. A model with 94% accuracy can fall to 78% in weeks; offline evaluation with held‑out test sets establishes a baseline before deployment.