Introduction to Machine Learning

Catalog description

An introduction to basic concepts in machine learning. Students will be introduced to the fundamental concepts and algorithms used by computers to solve real world problems. Topics include supervised learning (decision trees, logistic regression, neural networks, support vector machines), unsupervised learning (clustering, dimensionality reduction), deep learning, and reinforcement learning. Students will learn and implement various steps of machine learning in practical applications. Prerequisite(s): CMSC 262 and MATH 171 Corequisite(s): None