Applied Neural Computing (CMPE461) Course Details

Course Name: Applied Neural Computing
Code: CMPE461
Pre-requisite Course(s): MATH275
Objective: This course has the objective to provide an introduction to neural network architectures, learning algorithms, and their applications.
Content: Introduction to neural networks, perceptron learning rules, backpropagation algorithms, generalization and overtraining, adaptive linear filters, radial basis networks, self organizing networks, learning vector quantization, recurrent networks.
Term: Both
Theory: 2
Application: 0
Laboratory: 2
Credit: 3
Web:
ECTS Course File: Course File
Course File:
ECTS: 5