Course Schedule - Spring Semester 2018

     

ELEC 475 001 (CRN: 22346)

LEARNING FROM SENSOR DATA

Long Title: LEARNING FROM SENSOR DATA
Department: Electrical & Computer Eng.
Instructor: Aazhang, Behnaam
Meeting: 9:25AM - 10:40AM TR DCH 1070 (8-JAN-2018 - 20-APR-2018) 
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:
May not be enrolled in one of the following Level(s):
Graduate
Section Max Enrollment: 99
Section Enrolled: 10
Total Cross-list Max Enrollment: 99
Total Cross-list Enrolled: 31
Enrollment data as of: 19-SEP-2020 6:13PM
 
Fees: None
 
Final Exam: No Final Exam
Final Exam Time:
28-APR-2018  
9:00AM - 12:00PM S TBA TBA
 
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. Mutually Exclusive: Cannot register for ELEC 475 if student has credit for ELEC 575.