Neural Networks

The course gives an overview and a fundamental theoretical understanding of the most important neural net algorithms. These include models of associative memory algorithms for learning from examples (e.g., perceptron learning, back-propagation, temporal difference learning), and models for self-organization. Through comparison with methods from statistics and computer science students can develop an understanding of when neural networks are useful in application problems.