CISC 3440 Machine Learning
3 hours; 3 credits
An introduction to machine learning for students with some mathematical maturity. Topics include: machine learning in relation to artificial intelligence, data sources and characteristics, linear and non-linear regression, machine learning concepts like the bias-variance tradeoff, linear and non-linear classification, hidden Markov models and the expectation-maximization algorithm, unsupervised learning, and deep learning. Examples will be drawn from several domains including natural language processing.
Prerequisite: Computer and Information Science 3130 or 3225; MATH 2501 or 3501 or Computer and Information Science 2210.
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