Modul 11847

• All interested students are asked to please send an email until April 6, 2022 to  meer(at)b-tu.de indicating their wish to participate (no official regsitration yet). Please register aswell in Moodle for the course. Registration is already possible (no password required). It is at the moment not yet clear whether the course will be taught online or in presence, so please check frequently the course's webpage.
• If there are only German speaking students in the audience lectures can also be given in German if required.

Necessary official registration for the module online at the examination office.

Start of lectures: Week 15, first lecture on 12.04.2022

Exercises will start on 22.04.2022

There will be an oral exam, presumably in the second exam period 19.09. - 30.09.20. More details will be given during the course.

• E. Alpaydin: Maschinelles Lernen, Oldenbourg Verlag München, 2008
• M. Anthony, N.Biggs: Computational Learning Theory, Cambridge University Press 1997
• N. Christiani, J. Shawe-Taylor: An Introduction to Support Vector Machines and kernel-based Learning Methods, Cambridge Univ. Press,  2003
• A.C.C Coolen, R. Kühn, P. Sollich: Theory of Neural Information Processing Systems, Oxford University Press 2005
• P. Fischer: Algorithmisches Lernen, Teubner 1999
• P. Flach: Machine Learning: The Art and Science of Algorithms that Make Sense of Data, Cambridge University Press 2012
• F. M. Ham, I. Kostanic: Principles of Neurocomputing for Science & Engineering, McGraw Hill 2001
• S. Haykin: Neural Networks, Prentice Hall, 1999
• R. Rojas: Theorie der neuronalen Netze, Springer 1996
• S. Shalev-Shwartz, S. Ben-David: Understanding Machine Learning, Cambridge University Press 2014.

Some journals:

• Machine Learning, Springer
• Neural Networks, INNS, Elsevier
• Transactions on Neural Networks, IEEE