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Jul 05, 2025
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ECSE 4840 - Introduction to Machine Learning
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.
Prerequisite: (MATH 2010 or (MATH 2011 and MATH 2012)) and ECSE 2500 . Programming skills using MATLAB or Python is preferred.
When Offered: FALL TERM ANNUALLY
Graded: GRADED
Credit Hours: 3
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