This lecture is made up entirely from material from the start of the Neural Nets lecture and a subset of the topics in the “Favorite Regression Algorithms” lecture. We talk about linear regression, and then these topics: Varying noise, Non-linear regression (very briefly), Polynomial Regression, Radial Basis Functions, Robust Regression, Regression Trees, Multilinear Interpolation and MARS.