Machine Learning

Catalog description

This course introduces the principles, algorithms, and applications of machine learning. Students are exposed to machine learning through a blend of mathematical and statistical descriptions, hands-on programming exercises, and real-world engineering problems. Topics include, but are not limited to optimization, linear statistical models, kernel regression, neural networks, support vector machines, computer vision, and NLP.