Deep and Reinforcement Learning Fundamentals

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CAP 5619

Deep and Reinforcement Learning Fundamentals

Spring 2022

Note to CS and non-CS students: This course covers principles and algorithms of deep learning and reinforcement learning and does NOT cover how to train deep neural networks using deep learning frameworks. You need to be able to design and train deep neural networks using Keras or any other deep learning framework (such as TensorFlow and PyTorch).

Useful links and online information

Deep Learning Book by Ian Goodfellow and Yoshua Bengio and Aaron Courville.
Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto. (1st edition is available (html format only) from here)
Neural Networks and Deep Learning by Michael Nielsen, a free online book.
UC Irvine Machine Learning Repository.
Computer Vision Home Page
Face recognition homepage.
A Java Applet for computing Voronoi diagrams.
Statistical Pattern Recognition Toolbox.
Introduction to Probability -- Charles Grinstead and Laurie Snell.
Kernel Methods Homepage.
Introduction to Support Vector Machines.
DARPA Urban Challenge.
Journal of Machine Learning Research.
IEEExplore provides provides full-text access to IEEE transactions, journals, magazines and conference proceedings published since 1988 and all current IEEE Standards.
ACM Digital Library.
The Apache SpamAssassin Project.
Matlab online documents.
Introduction to Matlab ( http://ie.tamu.edu/people/faculty/butenko/INEN623/matlab.pdf).
Octave (similar to Matlab but is free).
The Weka Web Site.
Pattern Theory Group.
National Human Genome Research Institute.
Convolutional neural networks.
OpenDT (Decision tree and decision tree ensembles).
Commercial Tools for Bayesian Networks: HUGIN.
Commercial Tools for Bayesian Networks: AgenaRisk.
Bayesian Net Toolbox.
IBM Watson.
Building Watson.
Autonomous Car Driving through heavy City Traffic.

Important dates

Offered in Spring, 2022.
Class meeting time: Monday and Wednesday, 6:35PM-7:50PM, via the FLEX mode (in LOV 103 and via Zoom).

News and Announcements

The course is CAP 5619.
The course number is 9570.
Class meeting time: Monday and Wednesday, 6:35PM-7:50PM.
Meeting location: Room 103, Love Building and via zoom.

Handouts

The lecture notes along with additional handouts are available from the Weekly Calendar Page.

Assignments and Solutions

The assignments with their due dates are listed at from the Weekly Calendar Page; solutions will be made available as hardcopy.

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