A comprehensive guide to model evaluation in machine learning, explaining its "what, why, when, how, and who" and likening it to a rigorous quality control process for AI models. It also details common challenges in evaluating models, such as data issues and biases, and explains how Vertex AI functions as an all-in-one platform to mitigate these challenges and elevate MLOps maturity by integrating evaluation throughout the ML lifecycle