CGS4314 - Intelligent Systems Analysis

CGS 4314 Intelligent Systems Analysis (3 semester credit hours) This advanced machine learning course covers mathematics essential for the analysis and design covers mathematics essential for the analysis and design of unsupervised, supervised, and reinforcement machine learning algorithms including deep learning neural network models formulated within a statistical empirical risk minimization framework. Topics include: advanced vector and matrix calculus, stochastic sequences of mixed random vectors, Bayesian nets, and Markov fields. Unsupervised, supervised and reinforcement machine learning applications are emphasized through the course. Prerequisites: ((MATH 2414 or MATH 2419) and (CS 3341 or SE 3341) and MATH2418) or instructor consent required. (Same as CS 4314) (3-0) T