[rkp8000]

I love that Ridge Regression is introduced in the context of multicollinearity. It seems almost everyone these days learns about it as a regularization technique to prevent overfitting, but one of its fundamental use cases (and indeed its origin I believe) is in balancing weights among highly correlated (or nearly linearly dependent) predictors, which can cause huge problems even if you plenty of data.