Spring 2020 - ENSC 413 D100
Deep Learning Systems in Engineering (4)
Class Number: 8548
Delivery Method: In Person
Overview
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Course Times + Location:
Jan 6 – Apr 9, 2020: Tue, Thu, 2:30–4:20 p.m.
Burnaby
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Prerequisites:
MATH 251, ENSC 280, ENSC 351, ENSC 380.
Description
CALENDAR DESCRIPTION:
Machine learning basics, generalization theory, training, validation, and testing. Introduction to artificial neural networks: feedforward, convolutional, recurrent networks. Types of layers in deep models. Architectural and memory calculations. Regularization and optimization. Hardware architectures for deep learning. The course culminates in a major project focusing on engineering applications of deep learning. Students with credit for ENSC 813 may not take this course for further credit.
Registrar Notes:
SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.
Each student is responsible for his or her conduct as it affects the University community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS