INFR 3700U – Machine Learning

In this course, students learn 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, K-means, dimensionality reduction, neural networks, deep neural networks and TensorFlow. The course uses the Python programming language.
Credit hours: 3
Lecture hours: 3
Prerequisite(s): (INFR 1100U or INFR 1101U) and (INFR 2140U or INFR 2141U) and (INFR 1400U or BUSI 1450U)
Cross-listed: MITS 6800G