Advanced Learning From Data. 3 credits

Catalog description

Review of machine learning basics to motivate deep learning networks. Examines various deep learning network architectures and models in detail, including deep forward networks, convolutional networks, recurrent networks, and autoencoders. Discusses the training and implementation of deep models, such as hyper-parameter tuning, regularization, and optimization. Introduction of deep reinforcement learning. Involves course projects with a focus on the survey of applications, research problems, and new advances. Offered by Electrical & Comp. Engineering . May not be repeated for credit.