CSCE 4205 - Introduction to Machine Learning

3 hours

Theory and practice of machine learning. Linear regression, logistic regression, decision trees, neural network learning, support vector machines, kernel methods, bagging, boosting, random forests, ensemble learning, deep learning, unsupervised learning including k-means and hierarchical agglomerative clustering, semi-supervised learning, active learning, and reinforcement learning. Practical applications of machine learning algorithms. Topics in experimental design and computational learning theory.

Prerequisite(s): CSCE 3110 or with a grade of C or better. Non-CSE majors must have Instructor consent by email. As well as, Departmental Consent by filling out the Enrollment Assistance request form at www.cse.unt.edu/overrides. Please upload the instructor consent in the form.