CSC462 Fundamentals of Deep Learning

[3–0, 3 cr.]

This course presents an introduction to deep learning and its applications. Topics include introduction to neural networks, regularization, convolution neural networks, auto-encoders, recurrent neural networks, long short-term memory networks, generative adversarial networks, and reinforcement learning. An applied approach will be used, where students get hands-on exposure to AI techniques through the use of state-of-the-art machine learning software frameworks.

Note: This course has not been taught since Fall 2021 and will not be taught during the academic year 20234-2025.