Introduction to supervised learning. Linear models vs k-nearest neighbors. Training and test error. Bias and variance.
Slides here.
Trevor Hastie, Robert Tibshirani, Jerome Friedman: The Elements of Statistical Learning (2nd Edition), Ch. 2 (pp. 9-17, 28-29)
Leo Breiman: Statistical Modeling: The Two Cultures