Linear Mixed ModelCovers the linear mixed model, including fixed and random effects, estimation, and inference techniques.
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.
Nonparametric RegressionCovers nonparametric regression, scatterplot smoothing, kernel methods, and bias-variance tradeoff.
