CSE546: Machine Learning

Catalog Description: Explores 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.

Prerequisites: CSE 312, STAT 341, STAT 391 or equivalent.
Credits: 4.0

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