CSC413H1: Neural Networks and Deep Learning

Hours

24L/12T

Previous Course Number

CSC321H1/CSC421H1

An introduction to neural networks and deep learning. Backpropagation and automatic differentiation. Architectures: convolutional networks and recurrent neural networks. Methods for improving optimization and generalization. Neural networks for unsupervised and reinforcement learning.

Prerequisite
CSC311H1/​ CSC311H5/ CSCC11H3/ CSC411H1/ STA314H1/ ECE421H1/ ROB313H1/; MAT235Y1/​ MAT237Y1/​ MAT257Y1/ MAT257Y5/ MAT291H1/ MAT294H1/ AER210H1/ ( MAT232H5, MAT236H5)/ ( MAT233H5, MAT236H5)/ ( MATB41H3, MATB42H3); MAT223H1/ MAT240H1/ MAT185H1/ MAT188H1/ MAT223H5/ MATA23H3
Exclusion
CSC321H1/ CSC421H1, CSC321H5, CSC413H5. NOTE: Students not enrolled in the Computer Science Major or Specialist program at A&S, UTM, or UTSC, or the Data Science Specialist at A&S, are limited to a maximum of 1.5 credits in 300-/400-level CSC/ECE courses.
Distribution Requirements
Science
Breadth Requirements
The Physical and Mathematical Universes (5)
Mode of Delivery
In Class