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Init Facts 1

A practical guide to cross validation, why it matters, and how to choose the right strategy.

How neural networks learn features automatically, from raw inputs to useful representations.

A clear introduction to loss functions and how they guide model training.

A practical introduction to PCA: intuition, math, explained variance, and a scikit-learn example.