COMP 7745 - Machine Learning **

(3) An introduction to machine learning: hypothesis spaces, formation and evaluation; concept learning, decision trees, linear regression and perceptrons; graphical models (naÃ¯ve Bayes, Bayes Nets, Hidden Markov Models); computational learning theory; Support Vector Machines; instance-based learning. Grades of S, U, or IP will be given.