EEGR6365 - Neural Networks and Deep Learning

EEGR 6365 Neural Networks and Deep Learning (3 semester credit hours) This course covers the fundamentals of neural networks and deep learning. Perceptron, theory, and implementation of neural networks, back-propagation algorithm, theory of deep learning (loss functions, optimization, overfitting, regularization), deep neural networks, convolutional neural networks, autoencoders, sequential modeling, recurrent neural networks, long short-term memory networks, generative adversarial networks, transformers, diffusion models, deep learning applications; and deep learning evaluation. Prerequisites: Knowledge of probability and programming is required. (3-0) Y