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.
Repeat Status: Not repeatable for credit
Prerequisites: CS 504 [Min Grade: C]