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.
Portions of the CSE546 web may be reprinted or adapted for academic nonprofit purposes, providing the source is accurately quoted and duly creditied. The CSE546 Web: © 1993-2021, Department of Computer Science and Engineering, Univerity of Washington. Administrative information on CSE546 (authentication required).