Linear Models and OverfittingExplores linear models, overfitting, and the importance of feature expansion and adding more data to reduce overfitting.
Geometry and Least SquaresDiscusses the geometry of least squares, exploring row and column perspectives, hyperplanes, projections, residuals, and unique vectors.
Regularization TechniquesExplores regularization in linear models, including Ridge Regression and the Lasso, analytical solutions, and polynomial ridge regression.
Model Checking and ResidualsExplores model checking and residuals in regression analysis, emphasizing the importance of diagnostics for ensuring model validity.
Nonparametric RegressionCovers nonparametric regression, scatterplot smoothing, kernel methods, and bias-variance tradeoff.
