CSCI-B 555 MACHINE LEARNING (3 CR.)
Theory and practice of constructing algorithms that learn functions and choose optimal decisions from data and knowledge. Topics include: mathematical/probabilistic foundations, MAP classification/regression, linear and logistic regression, neural networks, support vector machines, Bayesian networks, tree models, committee machines, kernel functions, EM, density estimation, accuracy estimation, normalization, model selection.
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|LEC||3||13427||Open||2:30 p.m.–3:45 p.m.||MW||I E150||Tiganj Z
Regular Academic Session / In Person
LEC 13427: Total Seats: 50 / Available: 13 / Waitlisted: 0Show Details for section 13427