CSCI 547 - Machine Learning

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Introduction to the framework of learning from examples. Topics include various learning algorithms such as neural networks, Bayesian networks, and genetic algorithms, and generic learning principles such as bias/variance, MDL principle, and ethical considerations. Review statistical learning techniques, yet focuses on non-statistical techniques.

Prerequisite(s): CSCI 332