David W. Aha: Machine Learning Page - Comprehensive machine learning resources from Applications to Tutorials.

Knowledge Discovery Central - Knowledge Discovery Central is a Web portal and resource center for knowledge and information discovery from data. It encompasses areas such as Statistics, Data Mining, Knowledge Discovery in Databases, Machine Learning, Social Sciences, Marketing, and others.

Online Machine Learning Resources - Provided by the ML Group at the Austrian Research Institute for Artificial Intelligence (OFAI).

Machine Learning at AAAI - Starting point for online machine learning resources. Provided by the American Association for Artificial Intelligence.

Kernel machines - A central information source for the area of Support Vector Machines, Gaussian Process prediction, Mathematical Programming with Kernels, Regularization Networks, Reproducing Kernel Hilbert Spaces, and related methods. Provides links to papers, upcoming events, datasets, code.

Computational Learning Theory - A research field devoted to studying the design and analysis of algorithms for making predictions about the future based on past experiences. The emphasis in COLT is on rigorous mathematical analysis. COLT is largely concerned with computational and data efficiency.

Reinforcement Learning Repository - A centralized resource for researchers of reinforcement learning. Maintained at Michigan State University.

Boosting research - A website on Boosting and related ensemble learning methods. Provided links to papers, upcoming events, datasets, code, etc

Mixture Modelling page - Mixture modelling, Clustering, Intrinsic classification, Unsupervised learning and Mixture modeling. Links and bibliography.

Gowachin - A competition on Grammatical Inference.

Reasoning about Computational Resource Allocation - An introduction to "anytime" algorithms. Published in Crossroads, the student magazine of the ACM.

Machine Learning in Games - How computers can learn to get better at playing games. This site is for artificial intelligence researchers and intrepid game programmers. I describe game programs and their workings; they rely on heuristic search algorithms, neural networks, genetic algorithms, temporal differences, and other methods.

Machine Learning FAQ - Questions and answers about Machine Learning. Anyone can post his/her own questions and answers.

ILPnet2 - Network of Excellence in Inductive Logic Programming.

Grammatical Inference - Repository of information on grammatical inference, automata induction, and language acquisition.

Pattern Recognition Information - A hub for Pattern Recognition linking to journals, books, bibliographies, jobs, conferences and news.

Machine learning for user modeling - Resources for researchers and practitioners interested in the use of learning techniques in intelligent, user-adaptive systems.

Programming by Example - Programming by example (or by demonstration) is a technique for teaching the computer new behavior by demonstrating actions on concrete examples. The system records user actions and generalizes a program that can be used in new examples.

Pattern Recognition Course - Links to various Pattern recognition and machine learning resources

Recursive-Partitioning.com -- Supervised & Unsupervised Learning - Recursive partitioning based supervised and unsupervised learning methods resources. Comprehensive lists of classification trees, regression trees, rules induction, and clustering software packages. Extensive bibliography collection. Links to machine learning and data mining websites.

Group Method of Data Handling (GMDH) - Review of the GMDH approach for data mining and forecasting, with examples and software