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:
2025 Spring
| Section | Class Number | Schedule/Time | Instructor | Location | |
|---|---|---|---|---|---|
| 01 | 9482 | TuTh 4:00 - 5:15 pm |
Pomplun,Marc | University Hall Y04-4120 | |
|
Session:
Regular
Class Dates:
01/27/2025 - 05/14/2025
Capacity:
30
Enrolled:
0
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:
21
Status:
Open
Credits:
3/3
Class Notes:
Pre Requisites:
Pre-req = Permission of instructor
Course Attributes:
|
|||||