CMSC 478H - Introduction to Machine Learning

(3.00)

This course covers fundamental concepts, methodologies, and algorithms related to machine learning, which is the study of computer programs that improve some task with experience. Topics covered include decision trees, perceptrons, logistic regression, linear discriminant analysis, linear and non-linear regression, basic functions, support vector machines, neural networks, genetic algorithms, reinforcement learning, naive Bayes and Bayesian networks, bias/variance theory, ensemble methods, clustering, evaluation methodologies, and experiment design.

Course ID: 100216
Consent: Department Consent Required
Components: Lecture
Course Equivalents: CMSC 476
Requirement Group: You must have completed CMSC 471 with a grade of C or better.