DA 515 Introduction to Machine Learning
The course introduces principles, algorithms, and applications of machine learning from the point of view of modeling and prediction; formulation of learning problems; representation, over-fitting, generalization; clustering, classification, probabilistic modeling; and methods such as support vector machines, hidden Markov models, and Bayesian networks.
Cross Listed Courses
CSC 484,
CSC 584,
EE 484,
EE 584, DA 515
Prerequisite
DA 501 and DR 514