Deep Learning

Catalog description

Explores fundamental concepts including clustering and classification, logistic regression, linear regression, Support Vector Machines, and a variety of neural networks, including convolutional neural networks, recurrent neural networks, and memory-augmented neural networks. Investigates advanced machine learning topics including generative adversarial networks and deep reinforcement learning. Applies cutting-edge machine learning and deep learning techniques to address domain problems. Recommended Preparation: MATH 374 or MATH 264 ; MATH 260 ; and MATH 342 . Cross-listed: AI 478 and CS 478 are cross-listed. Students may not receive credit for both. Prerequisite(s): AI 330 or ( CS 311 and either MATH 264 or MATH 364 or MATH 374 ).