Introduction to Machine Learning

3 Credits

Techniques of applied machine learning rather than deep theory behind the algorithms and methods. Programming solutions for machine learning problems using a high-level programming language and associated machine learning libraries. Regression, clustering, principal component analysis, Bayesian methods, decision trees, random forests, support vector machines, and neural networks. This course is an undergraduate version of ISE 464 . A student cannot receive credit for both ISE 364 and ISE 464 . Prerequisites: CSE 003 or CSE 007 or CSE 017