Title of the course: Artificial Neural Networks
Instructor: Asst. Prof. Kerem Altun
Institution: Işık Ü.
Dates: 7-13 August 2017
Prerequisites: Basic level linear algebra and calculus. Introductory programming background is helpful but not necessary.
Level: Advanced undergraduate, beginning undergraduate
Abstract: Introduction to neural networks; basic neuron models; McCulloch-Pitts model; the perceptron; single-layer and
multi-layer feedforward networks; supervised learning and backpropagation; recurrent networks; Hopfield model;
unsupervised learning and Kohonen’s self-organizing feature maps; (if time permits) autoencoders, convolutional neural networks,
deep learning techniques.
Language: TR, EN