CSCI5527
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CSCI 5527 - Deep Learning: Models, Computation, and Applications (3 Cr.)
Computer Science and Engineering Administration (11108)
TIOT - College of Science and Engineering
Course description
This course introduces the basic ingredients of deep learning, describes effective models and computational principles, and samples important applications. Topics include universal approximation theorems, basics of numerical optimization, auto-differentiation, convolution neural networks, recurrent neural networks, generative neural networks, representation learning, and deep reinforcement learning.
prereq: CSCI 5521
Maturity in linear algebra, calculus, and basic probability is assumed. Familiarity with Python is necessary to complete the homework assignments and final project.
prereq: CSCI 5521
Maturity in linear algebra, calculus, and basic probability is assumed. Familiarity with Python is necessary to complete the homework assignments and final project.
Minimum credits
3
Maximum credits
3
Is this course repeatable?
No
Grading basis
OPT - Student Option
Lecture
Requirements
012034
Fulfills the writing intensive requirement?
No
Typically offered term(s)
Every Fall