Computer Science

Introduction to Deep Learning

Introduction to Deep Learning
Theory and practice of modern deep learning and associated software frameworks. A broad look at the field, drawing on material from machine vision, machine translation, dynamical systems, audio processing, neural computing and human perception. Supporting mathematical concepts are also covered, including linear algebra, stochastic optimization, and hardware acceleration.
 Hours3.0 Credit, 3.0 Lecture, 0.0 Lab
 PrerequisitesC S 312 & MATH 313; or C S 312 & MATH 213 & MATH 215
 ProgramsContaining C S 474
Course Outcomes: 

Please contact the individual department for outcome information.