Introduction to perceptron networks and history of neural networks. Neural network architectures. Perceptrons. Single layer neural networks. Multilayer neural networks. Learning rules. Backpropagation. Self-organizing maps. Convolutional neural networks. Recurrent neural networks.

Midterm - 35%
Homeworks - 20%
Participation - 5%
Final - 40%

(1) K. Mehrotra, C. Mohan and S. Ranka, Elements of Artificial Neural Networks, The MIT Press, 1996.

(1) M. Hagan, H. Demuth and M. Beale, Neural Network Design, PWS Publishing Company, 1996.
(2) S. Haykin, Neural Networks: A Comprehensive Foundation 2nd edition, Prentice Hall, 1999.
(3) L. V. Fausett, Fundamentals of Neural Networks: Architectures, Algorithms and Applications, Prentice Hall, 1993.

(1) Introduction to neural networks
(2) Neural network architectures
(3) Applications and evaluation
(4) Single layer neural networks
(5) Multilayer neural networks
(6) Training
(7) MLP applications
(8) Self-organizing maps
(9) Convolutional neural networks
(10) Recurrent neural networks

•  Introduction to neural networks - Slides
•  Neural network architectures - Slides
•  Applications and evaluation - Slides
•  Single layer neural networks - Slides
•  Multilayer neural networks - Slides
•  Training - Slides
•  MLP applications - Slides
•  Self-organizing maps - Slides
•  Convolutional neural networks - Slides
•  Recurrent neural networks - Slides