Week 1 Lecture 2 Supervised Learning

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Supervised learning, classification and regression, examples, linear mapping, quadratic mapping, performance, over-fitting, inductive biases – language bias, search bias, training set, test set, validation set, applications of supervised learning, sum-of-square error 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