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CS 613 Machine Learning 3.0 Credits

This course studies modern statistical machine learning with emphasis on Bayesian modeling and inference. Covered topics include fundamentals of probabilities and decision theory, regression, classification, graphical models, mixture models, clustering, expectation maximization, hidden Markov models, Kalman filtering, and linear dynamical systems.

College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: (CS 571 [Min Grade: C] or CS 503 [Min Grade: C]) and (CS 520 [Min Grade: C] or CS 502 [Min Grade: C]) and (CS 570 [Min Grade: C] or CS 501 [Min Grade: C]) and CS 504 [Min Grade: C]

Peace Engineering

...CS 502 CS 575 , CS 576 Machine Learning and AI : CS 510 , CS 613 , CS...

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