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Harvard CS50 AI Week 4: Learning — Supervised Learning, k-NN, SVM, Reinforcement Learning Q-learning & Nim

Week 4 enters ML: supervised classification (k-NN, SVM, Perceptron), model evaluation, RL basics (MDP, Q-learning, ε-greedy). Projects: Shopping (purchase prediction with k-NN) and Nim (learning to play via Q-learning).

Support Vector Machines: Margins, Duality, and SMO

Chapter 6 formalizes classification confidence as geometric margin, then builds an implementable SVM through Lagrange duality, kernels, and SMO.