Introduction to Machine Learning

ECSE-4840

A broad introduction to statistical machine learning. Topics include supervised learning: generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines; unsupervised learning: clustering, dimensionality reduction, kernel methods; learning theory: bias/variance tradeoffs, practical advice; online learning and reinforcement learning. Recent applications of machine learning, such as to data mining, robot navigation, speech recognition, image processing, and signal processing.

Past Term Data