Courses

CMSC 636: Neural Nets and Deep Learning

Topics ranging from fundamental learning rules, functional, cascade correlational, recurrent and gradient descent networks, to neocognitron, softmax, deep convolutional networks, autoencoders and pretrained deep learning (restricted Boltzmann machines). Students will be required to work in teams on a class paper.

Total Credit Hours: 3
Semester(s):
Spring 2020
Prerequisites:
grad standing in comp sci. assume undergrad-level knowledge in programming, algorithms, linear algebra, calculus and probability
Instructor:
Milos Manic
Instructor Email:
mmanic@vcu.edu

Weekly Live Sessions

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

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Questions? Contact the VCU CGEP Director:

Dr. Gregory Triplett   •   Ph: (804) 828-5387   •   getriplett@vcu.edu