Classical models built from the math you already know
Most models get one shot at training: fit, freeze, hope. Boosting refuses to stop there. Instead of training one model and stopping, it trains a whole relay of weak models, one after another, and each new one is aimed squarely at whatever the relay so far still gets wrong.
🔒 This is a Pro lesson — the interactive figure, worked examples, quiz and practice open with Pro access.
▶ Boosting: Learning from Your Mistakes