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COM S 474: Introduction to Machine Learning

(Dual-listed with COM S 574). (3-1) Cr. 3.

Prereq: COM S 311, STAT 330 or STAT 305, MATH 165, ENGL 250, SP CM 212; for graduate credit: graduate standing or permission of instructor
Introduction to tools and techniques of machine learning for applications. Selected machine learning techniques in practical data mining for classification, regression, and clustering, e.g., association rules, decision trees, linear models, Bayesian learning, support vector machines, artificial neural networks, instance-based learning, probabilistic graphical models, ensemble learning, and clustering algorithms. Selected applications in data mining and pattern recognition.

Agronomy

http://catalog.iastate.edu/collegeofagricultureandlifesciences/agronomy/

...BBMB, BIOL, CHEM, COM S, ECON, All Engineering...556, BIOL 472, BIOL 474, EEOB 570, EEOB...