Deep Learning

Catalog description

This course is an introduction to deep learning where algorithms extract layered high-level representations of data that maximizes performance on a given task. Topics covered include basic neural networks, convolutional and recurrent network structures, deep unsupervised and reinforcement learning, and applications to various problem domains (e.g. speech recognition, computer vision, hand writing recognition, etc). Three credits; one- hour laboratory. A pre requisite of AI 250 is required.