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ELEC 478

INTRODUCTION TO MACHINE LEARNING

Credit Hours: 3 · Undergraduate Upper-Level

This course is an advanced 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. Graduate/Undergraduate Equivalency: ELEC 578 . Mutually Exclusive: Cannot register for ELEC 478 if student has credit for COMP 540 / DSCI 303 / ELEC 578 / STAT 413 / STAT 613 .

Prerequisites & course information

Short Title: INTRO TO MACHINE LEARNING Department: Electrical & Computer Eng. Grade Mode: Standard Letter Course Type: Lecture Credit Hours: 3 Restrictions: Enrollment is limited to Undergraduate, Undergraduate Professional or Visiting Undergraduate level students. Course Level: Undergraduate Upper-Level Prerequisite(s): ( STAT 405 or CAAM 210 or CMOR 220 or COMP 140 or DSCI 101 ) and (CAAM 334 or CMOR 303 or CAAM 335 or CMOR 302 or MATH 355 or MATH 354 ) and ( ELEC 303 or DSCI 301 or STAT 310 or STAT 311 )

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