ECSE 4850 - Introduction to Deep Learning

Deep learning fundamentals and applications in artificial intelligence. Topics include machine learning foundation, linear regression and classification, deep neural networks, convolutional neural networks, recurrent neural networks, generative adversary neural networks, Bayesian neural networks, deep Boltzmann machine, deep Bayesian networks, and deep reinforcement learning.

Prerequisites/Corequisites: Prerequisites: ECSE 2500, (MATH 2010 or (MATH 2011 and MATH 2012)), and CSCI 1200.

When Offered: Spring term annually.

Co-Listed: ECSE 6850. Students cannot obtain credit for both this course and the cross listed course.

Credit Hours: 3

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ECSE 4850 - Introduction to Deep Learning