CSCI 252 - Neural Networks and Graphical Models

Institution:

Washington and Lee University

Subject:

Computer Science

Description:

Prerequisite: CSCI 112. A survey of the major developments in neural and belief networks, from the early perception models of the 1940s through the probabilistic Bayesian networks that are a “hot topic” in artificial intelligence today. Topics include the back-propagation algorithm, simple recurrent networks, Hopfield nets, Kohonen’s Self-Organizing Map, learning in Bayesian networks, and Dynamic Bayesian Networks, with readings from both popular textbooks and the scholarly literature. A major focus of the course is on writing programs to implement and apply these algorithms. Levy.

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.wlu.edu/

Phone Number:

(540) 458-8400

Regional Accreditation:

Southern Association of Colleges and Schools

Calendar System:

Semester

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