Course Schedule and Catalog

Department: Electrical & Computer Eng.

Meeting: 2:00PM - 3:15PM MF DCH Sym II Lab (23-AUG-2021 - 3-DEC-2021) 

Session: Full Term

Grade Mode: Standard Letter

Course Type: Lecture

Language of Instruction: Taught in English

Method of Instruction: Face to Face

Credit Hours: 3

 

Section Max Enrollment: 29

Section Enrolled: 15

Enrollment data as of: 26-MAR-2023 7:20PM

 

 

Final Exam: GR Course-Dept Schedules Exam

 

Description: Machine learning is in tremendous demand in numerous applications; however, its often prohibitive complexity remains a major challenge for its extensive deployment in resource constrained platforms. This course will introduce techniques which enable the development of energy/time efficient machine learning systems, taking a path from algorithm to architecture down to the circuit level. In particular, you will first learn commonly used machine learning algorithms, and then algorithm-, architecture-, circuit-level techniques for reducing the energy/time cost of machine learning systems while maintaining their powerful performance. Finally, we will do a deep dive into state-of-the-art efficient machine learning systems, such as Google's TPU and Eyeriss.