Introduction to Machine Learning

Catalog description

A broad introduction to machine learning and data mining. Topics include supervised learning (feature selection, Bayesian classifier, nearest neighbors, logistic regression, decision trees, support vector machines) and unsupervised learning (dimensionality reduction, k-means clustering, hierarchical clustering, principal component analysis) methods. Prerequisite: ( CSE 1001 or CSE 1502 ) and ( MTH 2201 or MTH 2202 or MTH 3102 or MTH 3200 )