EECE 580ENeural Network & Deep Learning

Catalog

In this course, we focus on the introduction of neural networks as well as their applications in deep learning. Fundamentals of neural networks and deep learning will be discussed, including multilayer perceptron, back-propagation algorithm, regularization theory, convolutional neural networks, recurrent neural networks, and reinforcement learning. After a brief overview of the python programming language and statistical signal processing, neural networks and their applications are followed. Application topics in speech recognition, image and language processing will be described. A final project will let students to work on the applications of deep learning or participate in online deep learning competitions. Prerequisite: EECE301 or equivalent signal and system knowledge. 3 credits.