Description
An introduction to neural networks and deep learning. Theory and application of Neural Networks to problems in machine learning. Various network architectures will be discussed. Methods for improving optimization and generalization of neural networks. Neural networks for unsupervised learning.
Prerequisites
- Prerequisite(s): ( COMP 3105 or SYSC 4415 ) and ( MATH 1104 or MATH 1107 ).
Conditions and arrangements
- Precludes additional credit for Precludes additional credit for COMP 5206 .
- Prerequisite(s): ( COMP 3105 or SYSC 4415 ) and ( MATH 1104 or MATH 1107 ).
- Lectures three hours a week.
Reference text in its original language
An introduction to neural networks and deep learning. Theory and application of Neural Networks to problems in machine learning. Various network architectures will be discussed. Methods for improving optimization and generalization of neural networks. Neural networks for unsupervised learning.
- Prerequisite(s): ( COMP 3105 or SYSC 4415 ) and ( MATH 1104 or MATH 1107 ).
- Precludes additional credit for Precludes additional credit for COMP 5206 .
- Lectures three hours a week.
Sources and references
Dates and sources are retained to help you verify the information. Translations are provided to facilitate reading; the official source governs conditions and requirements.
Source reference : https://calendar.carleton.ca/undergrad/courses/COMP/