Course Schedule - Fall Semester 2019

     

ELEC 515 001 (CRN: 13290)

EMBEDDED MACHINE LEARNING

Long Title: MACHINE LEARNING FOR RESOURCE-CONSTRAINED PLATFORMS
Department: Electrical & Computer Eng.
Instructor: Lin, Yingyan
Meetings:
9:30AM - 10:45AM W BRK 103 (26-AUG-2019 - 6-DEC-2019) 
9:40AM - 10:55AM M BRK 103 (26-AUG-2019 - 6-DEC-2019) 
Session: Full Term
Grade Mode: Standard Letter
Course Type: Lecture
Method of Instruction: Face to Face
Credit Hours: 3
Course Syllabus:
Course Materials: Rice Campus Store
 
Restrictions:
Must be enrolled in one of the following Level(s):
Graduate
Section Max Enrollment: 30
Section Enrolled: 6
Enrollment data as of: 2-APR-2020 9:13PM
 
Fees: None
 
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.