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rougier
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A collection of stand-alone Python machine learning recipes

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Machine Learning Recipes

This is a collection of stand-alone Python examples of machine learning algorithms. Run a specific recipe to see usage and result. Feel free to contribute an example (recipe should be reasonably small, including usage).

Multi-armed bandit (MAB)

  • Epsilon greedy (recipes/MAB/greedy.py)

    Sutton, Richard S., Barto, Andrew G. "Reinforcement Learning: An Introduction", MIT Press, Cambridge, MA (1998).

  • Softmax (recipes/MAB/softmax.py)

    Luce, R. Duncan. (1963). "Detection and recognition". In Luce, R. Duncan, Bush, Robert. R. & Galanter, Eugene (Eds.), "Handbook of mathematical psychology" (Vol. 1), New York: Wiley.

  • Thompson sampling (recipes/MAB/thompson.py)

    Thompson, William R. On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika, 25(3–4):285–294, 1933. DOI: 10.2307/2332286

  • Upper Confidence Bound (recipes/MAB/ucb.py)

    Lai, T.L and Robbins, Herbert, "Asymptotically efficient adaptive allocation rules", Advances in Applied Mathematics 6:1, (1985) DOI: 10.1016/0196-8858(85)90002-8

Artificial Neural Network (ANN)

Grossberg, Stephen (1987). Competitive learning: From interactive activation to adaptive resonance, Cognitive Science, 11, 23-63.

Jaeger, Herbert (2001) The "echo state" approach to analysing and training recurrent neural networks. GMD Report 148, GMD - German National Research Institute for Computer Science.

Elman, Jeffrey L. (1990). Finding structure in time. Cognitive Science, 14:179–211.

Hochreiter, Sepp and Schmidhuber, Jürgen (1997) Long Short-Term Memory, Neural Computation Vol. 9, 1735-1780

Rumelhart, David E., Hinton, Geoffrey E. and Williams, Ronald J. "Learning Internal Representations by Error Propagation". Rumelhart, David E., McClelland, James L., and the PDP research group. (editors), Parallel distributed processing: Explorations in the microstructure of cognition, Volume 1: Foundation. MIT Press, 1986.

Rosenblatt, Frank (1958), "The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain", Cornell Aeronautical Laboratory, Psychological Review, v65, No. 6, pp. 386–408. DOI:10.1037/h0042519

Aizerman, M. A., Braverman, E. A. and Rozonoer, L.. " Theoretical foundations of the potential function method in pattern recognition learning.." Paper presented at the meeting of the Automation and Remote Control,, 1964.

Y. Freund, R. E. Schapire. "Large margin classification using the perceptron algorithm". In: 11th Annual Conference on Computational Learning Theory, New York, NY, 209-217, 1998. DOI:10.1023/A:1007662407062

Kohonen, Teuvo. Self-Organization and Associative Memory. Springer, Berlin, 1984.

Markov Decision Process (MDP)

Bellman, Richard (1957). "A Markovian Decision Process". Journal of Mathematics and Mechanics. 6.

Dimensionality Reduction (DR)

Pearson, K. (1901). "On Lines and Planes of Closest Fit to Systems of Points in Space". Philosophical Magazine. 2 (11): 559–572. DOI:10.1080/14786440109462720

M. Turk & A. Pentland (1991) Eigenfaces for Recognition. Journal of cognitive neuroscience, 3(1): 71-86. DOI:10.1162/jocn.1991.3.1.71

W.S. Torgerson (1952) Multidimensional scaling: I. Theory and method Psychometrika, 17: 401-419 DOI:10.1007/BF02288916

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