|Neuronale Netzwerke A, WS 2006|
|Institut für Grundlagen der Informationsverarbeitung (708)|
The dramatic growth in practical applications for machine learning over the last ten years has been accompanied by many important developments in the underlying algorithms and techniques. In this course, basic machine learning techniques (so-called ''neural'' techniques, or simply neural networks) and recently introduced advanced techniques such as Deep Belief Networks and Gaussian Processes will be discussed. The student will gain a deep understanding of these techniques and learn to apply them for practical applications. We will adopt a modern view on neural networks based on Bayesian methods.
The following topics will be discussed:
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|13.03.12||Here is the outcome of the first exam. If you want to discuss your solutions, send an email to firstname.lastname@example.org until Thursday 15.3.2012.|
|31.01.12||Here is a sample test.|
|19.09.11||Homepage installed. If you have any questions, send an e-mail.|