Course Schedule and Catalog
Course Schedule - Spring Semester 2016
Meeting location information can now be found on student schedules in ESTHER (for students) or on the Course Roster in ESTHER (for faculty and instructors).Additional information available here.
Meeting location information can now be found on student schedules in ESTHER (for students) or on the Course Roster in ESTHER (for faculty and instructors).Additional information available here.
ELEC 575 001 (CRN: 25314)
LEARNING FROM SENSOR DATA
Long Title: LEARNING FROM SENSOR DATA
Department: Electrical & Computer Eng.
Instructor: Baraniuk, Richard G
Meeting: 2:30PM - 3:45PM TR (11-JAN-2016 - 22-APR-2016)
Part of Term: Full Term
Grade Mode: Standard Letter
Course Type: Lecture
Language of Instruction: Taught in English
Method of Instruction: Face to Face
Credit Hours: 3
Course Syllabus:
Restrictions:
Must be enrolled in one of the following Level(s):
Graduate
Section Max Enrollment: 99
Section Enrolled: 31
Total Cross-list Max Enrollment: 99
Total Cross-list Enrolled: 54
Enrollment data as of: 19-APR-2024 6:33PM
Final Exam: GR Course-Dept Schedules Exam
Final Exam Time:
4-MAY-2016
9:00AM - 12:00PM W
Description: The first half of this course develops the basic machine learning tools for signals images, and other data acquired from sensors. Tools covered include principal components analysis, regression, support vector machines, neural networks, and deep learning. The second half of this course overviews a number of applications of sensor data science in neuroscience, image and video processing, and machine vision. Additional course work required beyond the undergraduate course requirements. Cross-list: ELEC 475. Mutually Exclusive: Cannot register for ELEC 575 if student has credit for ELEC 475.