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Neural Networks

Course #: CS 672

Description:
An introduction to artificial neural networks. Topics include a survey of natural neural network models, perceptrons and their limitations, multi-layer networks and back propagation, Hebbian learning, unsupervised competitive learning, relations to automata and computability theory, adaptive resonance theory, applications of connectionist models of computing to various domains, including pattern recognition and databases.

Pre Requisites: Pre-req = Permission of instructor

Offered in:

2024 Spring

Section Class Number Schedule/Time Instructor Location
01 10072 TuTh
4:00 - 5:15 pm
Pomplun,Marc McCormack M01-0420
Session: Regular
Class Dates: 01/22/2024 - 05/08/2024
Capacity: 30
Enrolled: 14
Status: Open
Credits: 3/3
Class Notes:
Pre Requisites: Pre-req = Permission of instructor
Course Attributes:

2023 Fall

Section Class Number Schedule/Time Instructor Location
02 14550 TuTh
7:00 - 8:15 pm
Pei,Shichao McCormack M02-0404
Session: Regular
Class Dates: 09/05/2023 - 12/13/2023
Capacity: 40
Enrolled: 29
Status: Open
Credits: 3/3
Class Notes:
Pre Requisites: Pre-req = Permission of instructor
Course Attributes:

2024 Fall

Section Class Number Schedule/Time Instructor Location
02 4729 TuTh
4:00 - 5:15 pm
Pomplun,Marc HLL-3507 Media Auditorium
Session: Regular
Class Dates: 09/03/2024 - 12/13/2024
Capacity: 40
Enrolled: 9
Status: Open
Credits: 3/3
Class Notes:
Pre Requisites: Pre-req = Permission of instructor
Course Attributes: