Prerequisites: COMP 379 or STAT 338 or STAT 308
This course covers key concepts of neural network algorithms as well as their
applications in computer vision and natural language processing. The topics will include popular building blocks of neural networks including fully-connected, convolutional, recurrent, attention, and transformer layers.
Outcomes: Learn how to build and analyze popular modern neural network architectures; Learn how to design, build, and evaluate their models in the context of practical applications related to fields such as computer vision and natural language processing.
This course covers key concepts of neural network algorithms as well as their
applications in computer vision and natural language processing. The topics will include popular building blocks of neural networks including fully-connected, convolutional, recurrent, attention, and transformer layers.
Outcomes: Learn how to build and analyze popular modern neural network architectures; Learn how to design, build, and evaluate their models in the context of practical applications related to fields such as computer vision and natural language processing.