- AAAI (American Association for AI National Conference)
- ECML-PKDD (European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases)
- IJCAI (International Joint Conferences on Artificial Intelligence)
- MLMTA International Conference on Machine Learning: Models, Technologies & Applications
- NIPS (Neural Information Processing Systems)
- UAI (Association for Uncertainty in Artificial Intelligence)
Books & Papers
- Probabilistic Graphical Models: Principles and Techniques, Daphne Koller, Nir Friedman, The MIT Press, 2009. [url]
- Introduction to Machine Learning (Adaptive Computation and Machine Learning series), Ethem Alpaydin, The MIT Press, 2009. [url]
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Trevor Hastie, Robert Tibshirani, Jerome Friedman, Springer, 2009. [url]
- Pattern Recognition and Machine Learning , Christopher M. Bishop, Springer, 2006.
- Information Theory, Inference and Learning Algorithms, David J. C. MacKay, Cambridge University Press, 2003. [url]
- Pattern Classification, 2nd Edition , Richard O. Duda, Peter E. Hart, David G. Stork, A Wiley-Interscience Publication, 2001.
- Machine Learning, Tom M. Mitchell, McGraw Hill, 1997.
- Reinforcement Learning: A Survey, L. P. Kaelbling, M. L. Littman, A. W. Moore, Journal of Artificial Intelligence Research, 4:237–285, 1996. [pdf]
- Machine Learning, Thomas G. Dietterich, Annual Review of Computer Science, 4:255–306, 1990. [pdf]
- The Prospective studentí»s Introduction to the Robot Learning Problem , U. Nehmzow, T. Mitchell , Technical Report UMCS-95-12-6, University of Manchester, 1990. [pdf]
- MATLAB (widely used program for performing numerical calculations)
- mloss (machine learning open source software)
- Shogun (an large scale machine learning toolbox that provides several SVM implementations)
- Weka (a suite of machine learning software written at the University of Waikato)
This page is maintained by Sang-Woo Lee (email@example.com).
Last update: January 10, 2012.