SS 2006

Neural Networks and Machine Learning:
Contents

Date Topics
24.4.06 Neural Networks: (Script)
Supervised learning
Gradient descent for a single unit network
Multilayer Networks
Backpropagation Algorithm
8.5.06 Examples for Applications of
Neural Networks 		The sound example of the network that learns to read (NETtalk), can be found here .
Bias-Variance Dilemma
11.5.06 Reinforcement Learning Not relevant for the exam!
15.5.06 Support-Vector Machines (Script)
22.5.06 Nonlinear Expansion (Script)
Kernel Trick (Script)
29.5.06 Probability Theory and Bayesian Theory (Script)
12.6.06 Graphical Representations of Bayesian Networks (Script)
19.6.06 Inference in Gibbsian Networks (Script)
26.6.06 Learning in Bayesian Networks (Script)
3.7.06 Principal Component Analysis I (Script)
10.7.06 Principal Component Analysis II (Script)
Henning Sprekeler, http://itb.biologie.hu-berlin.de/~sprekeler/