Model Evaluation Metrics

This lesson focuses on how AI and machine learning models are evaluated and measured. Students learn key metrics including accuracy, precision, recall, F1 score, ROC-AUC, and confusion matrices. The lesson also introduces important concepts such as overfitting, underfitting, and the bias-variance tradeoff, helping learners understand how to assess model reliability and performance.