Course Catalog - 2019-2020

     

ELEC 478 - INTRO TO MACHINE LEARNING

Long Title: INTRODUCTION TO MACHINE LEARNING
Department: Electrical & Computer Eng.
Grade Mode: Standard Letter
Language of Instruction: Taught in English
Course Type: Lecture
Credit Hours: 3
Restrictions:
Must be enrolled in one of the following Level(s):
Undergraduate Professional
Visiting Undergraduate
Undergraduate
Prerequisite(s): (STAT 405 OR CAAM 210 OR COMP 140) AND (CAAM 335 OR MATH 355)
Description: The course provides an introduction to concepts, methods, best practices, and theoretical foundations of machine learning. Topics covered include regression, classification, kernels, clustering, decision trees, ensemble learning, empirical risk minimization and regularization, and learning theory. Graduate/Undergraduate Equivalency: ELEC 578. Recommended Prerequisite(s): ELEC 301 and ELEC 475. Mutually Exclusive: Cannot register for ELEC 478 if student has credit for DSCI 303/ELEC 578.