MITS 6800G - Machine Learning

Students will learn the mathematical foundations of machine learning and how to program a computer system to make predictions on, classify, or cluster data that the system has never seen before. Topics include theory and practice of supervised and unsupervised learning, covering well-known algorithms such as ordinary and penalized linear regression, Naïve Bayes, support vector machines, ensemble methods and K-means.
Credit hours: 3
Cross-listed: INFR 3700U