CSE446: Machine Learning

Catalog Description: Methods for designing systems that learn from data and improve with experience. Supervised learning and predictive modeling: decision trees, rule induction, nearest neighbors, Bayesian methods, neural networks, support vector machines, and model ensembles. Unsupervised learning and clustering. Prerequisite: CSE 332; either STAT 390, STAT 391, or CSE 312.

Prerequisites: CSE 332; either STAT 390, STAT 391, or CSE 312
Credits: 4.0

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