Units: 4 Terms Offered: FaSpMathematical aspects of Machine Learning. PAC Learning, VC-dimension and complexity. Linear predictors (regression, perceptron, SVM). Convex learning and gradient descent. Neural networks and backpropagation. Prerequisite: (MATH 226g or MATH 227 or MATH 229) and (MATH 208x or MATH 407) and (MATH 225 or MATH 245) Instruction Mode: Lecture Grading Option: Letter
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