CMSC 591: Deep Neural Networks

Topics ranging from fundamental learning rules, functional, cascade correlational, recurrent and gradient descent networks, to neocognitron, softmax, deep convolutional networks, autoencoders, and pre-trained deep learning (restricted boltzmann machines). Students will be required to work in teams on class paper. The course will assume undergraduate-level background in programming, algorithms, linear algebra, calculus, statistics, and probability. Prerequisites: Graduate student standing in computer science or acceptance into accelerated B.S. to M.S. program in computer science.

Total Credit Hours: 3
Spring 2017
Milos Manic
Instructor Email:

Weekly Live Sessions

Mon Tue Wed Thu Fri Sat
3:30-4:45 PM 3:30-4:45 PM

Back to Search Results

Questions? Contact the VCU CGEP Director:

Dr. Gregory Triplett   •   Ph: (804) 828-5387   •