COSC 4P80 Artificial Neural Network:Outline
Winter 2017
Department of Computer Science
Brock University
Instructor: Beatrice
M.Ombuki-Berman
Office:J307, office hrs: Tue. 11:45 pm - 12:15 pm (or appointment)
E-mail:bombuki@brocku.ca
Teaching Assistant: Andrew Runka E-mail:ar03gg@badger.ac.brocku.ca
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Course Description
The goal of this course is to introduce students to practical problem
solving using a powerful
class of AI model, the neural network.
We begin with a brief introduction of a loose analogy to
the brain to
give some idea of the parallel and distributed nature of neural
networks.
An overview of various neural network models will be carried out by
discussing
the underlying
principles,
model architectures, behaviours and learning algorithms. A range of
applications will also be discussed.
Prerequisites:
- Programming skills are assumed.
- Completion of
COSC 3P71 Introduction to Artificial Intelligence is
highly recommended.
- Familiarity with linear algebra, basic calculus, probaility theory
and statistics is expected.
Where necessary, and if possible, some
fundamental refreshers on some of these will be provided via
tutorials.
Textbook (TBA):
There will be no main text, however, we will uses various resources
including following texts.
- Kishan Mehrotra, Chilukuri K. Mohan and Sanjay Ranka.
Elements of Artificial Neural Networks. ISBN: 0-262-13328-8.
- Fausett, L. Fundamentals of Neural Networks. New York:
Prentice Hall.
- Haykin, S. Neural Networks: A Comprehensive Foundation. New
York: Macmillan Publishing.
- Duda et al. Pattern Classification (2ed.). Wiley & Sons, Inc
Evaluation
| Assignments (2) |
35 % |
| Term Project |
25% |
| Class Test (March tba) |
15% |
| Seminars & Participation |
20% |
| labs |
5% |