Overfitting, Cross-validation & Regularization

This lecture covers the concepts of model complexity, overfitting, and the importance of cross-validation and regularization in machine learning. It explains the impact of different strategies on model performance and provides insights into handling nonlinear data through techniques like k-Nearest Neighbors and polynomial curve fitting.