Neural Networks

April 20th, 2014

ECOM 6343: Neural Networks (graduate level)   F

Course Description:   F

fundamental Concepts of Neural Computing, Terminology, Main Neural Networks Architecture Single/Multilayer Perceptrons, Feedback(Recurrent)/ Feedforward Information Flow, Supervised/ Unsupervised Learning Models, Backpropagation, Self-Organizing, Adaptive Resonance, Auto/Heteroassociation Neural Memory Models, Neurocomputing Implementation, Applications, Performance Evaluation.  F

Prerequisite: ECOM 3312 Data Structures and Algorithms

Lectures:  Syllabus and Ch1

                              Introduction to Machine learning                 

       All complete lectures are uploaded on moodle

textbook:  http://ar.scribd.com/doc/74013387/Neural-Network-Design-by-Martin-T-Hagan

: Additional Useful Webpages for Neural network

d[1]  Introduction to Neural Networks Course

r [2] Neural Networks

t [3] Lectures on Neural Networks

o [4] Building a Neural Net Simulator in C++ v