Course Schedule - Spring Semester 2024

     

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 475 001 (CRN: 20719)

LEARNING FROM SENSOR DATA

Long Title: LEARNING FROM SENSOR DATA
Department: Electrical & Computer Eng.
Instructor: Azhang, Behnam
Meeting: 9:25AM - 10:40AM TR (8-JAN-2024 - 19-APR-2024) 
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:
Course Materials: Rice Campus Store
 
Restrictions:
Must be enrolled in one of the following Level(s):
Undergraduate Professional
Visiting Undergraduate
Undergraduate
Prerequisites: ELEC 303 OR DSCI 301 OR STAT 310 OR STAT 311
Section Max Enrollment: 99
Section Enrolled: 24
Total Cross-list Max Enrollment: 99
Total Cross-list Enrolled: 52
Enrollment data as of: 2-JUL-2024 3:07PM
 
Additional Fees: None
 
Final Exam: No Final Exam
Final Exam Time:
26-APR-2024  
2:00PM - 5:00PM F
 
Description: Basic information theoretic metrics and probabilistic machine learning tools for signals, images, and other data acquired from sensors, including graphical models, density estimation, principal components analysis, support vector machines, and source separation. Graduate/Undergraduate Equivalency: ELEC 575. Mutually Exclusive: Cannot register for ELEC 475 if student has credit for ELEC 575. Cross-list: ELEC 575. Mutually Exclusive: Cannot register for ELEC 475 if student has credit for ELEC 575.