Deep Learning for Engineers.

Catalog description

This is an introductory course for Deep learning. The students will become familiar with the mathematical background, applications, and limitations of popularly used deep neural network architectures for supervised deep learning tasks. Students will be expected to write codes in standard programming languages. Students without programming experience will be given directed readings and tutorials to cope up with the coding part of this course. Prereq: ENGR 729 Machine Learning for Engineers is the prerequisite for this course. Alternatively, graduate students in any department with good mathematical/ coding/ AI background can request the instructor to waive the prerequisite.