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CSCI 5622 (3). Machine Learning

Trains students to build computer systems that learn from experience. Includes the three main subfields: supervised learning, reinforcement learning and unsupervised learning. Emphasizes practical and theoretical understanding of the most widely used algorithms (neural networks, decision trees, support vector machines, Q-learning). Covers connections to data mining and statistical modeling. A strong foundation in probability, statistics, multivariate calculus, and linear algebra is highly recommended. Prerequisites: Graduate standing or consent of instructor.

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Department of Computer Science
University of Colorado Boulder
Boulder, CO 80309-0430 USA
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May 5, 2012 (14:25)
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