Classical ML¶
Before deep learning existed — and still, in 2026, the right default for tabular data (spreadsheets, database tables, log-derived feature stores) — "classical" machine learning covers two families: supervised models, which learn a mapping from features to a label from labeled examples, and unsupervised models, which find structure in unlabeled data. This chapter is the mathematical and practical core of Part IX ("Artificial Intelligence"): every algorithm below is derived from its objective function, solved (in closed form where one exists, else by an explicit iterative procedure), and then computed on small numbers you can check by hand. …
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