Connectionists: teaching material on basic math and machine learning available

[Laurenz Wiskott]

Dear All,

I have put a large part of my teaching material on basic math and machine learning online
at

  https://www.ini.rub.de/PEOPLE/wiskott/Teaching/Material/index.html

It contains lecture notes, lecture videos, analytical exercises and solutions, and
python programming exercises and solutions on the following topics:

  Backpropagation
  Bayesian theory and graphical models
  Bias-variance dilemma
  Clustering
  Differential equations
  Fisher discriminant analysis
  Functions
  Independent component analysis
  Information theory
  Kernel trick
  Linear algebra
  Linear regression
  Multiple integrals
  Nonlinear expansion
  Optimization - analytical methods
  Optimization - numerical methods
  Principal component analysis
  Reinforcement learning
  Restricted Boltzmann machines
  Self-organizing maps
  Slow feature analysis - applications
  Support vector machines
  Vector quantization

The level is somewhat mixed and some material is incomplete, but might still be useful.

Please feel free to use, share, and modify under the terms of the corresponding license,
usually a creative commons license.

Best wishes,

Laurenz Wiskott.

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 Prof. Dr. Laurenz Wiskott, Institut für Neuroinformatik, RUB Bochum, Germany, EU 
 +49/234/32-27997, https://www.ini.rub.de/PEOPLE/wiskott/, laurenz.wiskott at rub.de 
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