23  Regression Under Heavy Tails

Builds least squares, then least-absolute-deviations, then Huber regression via gradient descent, fitting all three to the same outlier-contaminated dataset and comparing the resulting slopes side by side — a direct, visual demonstration of Chapter 20’s abstract point.