Course Schedule - Fall Semester 2020

     

ELEC 578 001 (CRN: 16361)

INTRO TO MACHINE LEARNING

Long Title: INTRODUCTION TO MACHINE LEARNING
Department: Electrical & Computer Eng.
Instructors:
Allen, Genevera I.
Barman, Arko
Meeting: 4:50PM - 6:10PM TR ANH 117 (24-AUG-2020 - 4-DEC-2020) 
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
Course Syllabus:
Course Materials: Rice Campus Store
 
Restrictions:
Must be enrolled in one of the following Level(s):
Graduate
Section Max Enrollment: 0 (permission required)
Section Enrolled: 3
Enrollment data as of: 28-FEB-2024 10:10AM
 
Additional Fees: None
 
Final Exam: GR Course-Dept Schedules Exam
 
Description: This course is a graduate level introduction to concepts, methods, best practices, and theoretical foundations of machine learning. Topics covered include regression, classification, regularization, kernels, clustering, dimension reduction, decision trees, ensemble learning, and neural networks. Additional work is required for graduate students beyond the undergraduate requirement. Recommended Prerequisite(s): Basic statistics and probability, linear algebra, and programming in R or Python are required. Mutually Exclusive: Cannot register for ELEC 578 if student has credit for DSCI 303/ELEC 478.