CSC413H1: Neural Networks and Deep Learning

Previous Course Number: 
CSC321H1/CSC421H1
Hours: 
24L/12T

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/​​ CSC411H1/​ STA314H1/​ ECE421H1/​ ROB313H1/​ CSCC11H3; MAT235Y1/​​ MAT237Y1/​​ MAT257Y1/​ MAT291H1/​ MAT294H1/​ AER210H1/​ MAT232H5/ MAT233H5/ MATB41H3; MAT221H1/​ MAT223H1/​ MAT240H1/​ MAT185H1/​ MAT188H1/​ MAT223H5/ MATA23H3

Exclusion: 

CSC321H1/​CSC421H1. NOTE: Students not enrolled in the Computer Science Major or Specialist program at the FAS, UTM, or UTSC, or the Data Science Specialist at FAS, are limited to a maximum of three 300-/400-level CSC/ECE half-courses.

Distribution Requirements: 
Science
Breadth Requirements: 
The Physical and Mathematical Universes (5)