Model Selection Criteria: AIC, BIC, Cp

This lecture covers model selection criteria such as AIC, BIC, and Cp, used in statistics for data science. It explains the concepts of model selection, prediction error, and the bias-variance tradeoff, providing insights into the tradeoffs between model complexity and accuracy.