Credit units: 3
Weekly hours: 3 Lecture hours
College: Arts and Science
Department: Computer Science
A survey of Deep Learning techniques and their application to problems in computer vision and data science. Deep learning techniques may include Deep Neural Networks, Convolutional Neural Networks, Recurrent Networks, Deep Generative Models and Reinforcement Learning. Application domains will focus on computer vision problems, including image classification, object detection and image segmentation. Additional application domains in natural language processing and robotics control will be introduced. Software tools will be introduced for practical application.
Prerequisite(s): MATH 164, MATH 266, EE 216, or CE 318; and STAT 245; and CMPT 317 or CMPT 487
Note: Students with credit for CMPT 828 or CMPT 498.3 Deep Learning and Applications may not take this course for credit.
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