Intermediate Deep Learning for Engineers

6 units · Graduate

Spring: 6 units This course will introduce some of the advances in deep learning technology such as sequential learning using Recurrent Neural Networks, Generative Adversarial Networks, Attention models and Transformers, and Diffusion models. Students will learn how to implement these models using deep learning libraries (Pytorch). Introduction to deep learning is the prerequisite. Prerequisites: (11-785 or 24-787 or 10-601 or 10-715) and ( 24-788 or 11-785) Course Website: http://www.cmu.edu/me/graduate/index.html