See also:

• Computers: Artificial Intelligence: Belief Networks  (52)
• Computers: Artificial Intelligence: Machine Learning  (239)
• Computers: Artificial Intelligence: Vision  (62)
• Computers: Artificial Life  (269)
• Health: Medicine: Medical Specialties: Neurology  (373)
• Science: Biology: Neurobiology  (315)
• Science: Math: Statistics: Bayesian Analysis  (20)
• Science: Social Sciences: Cognitive Science  (270)
• Science: Social Sciences: Psychology: Neuropsychology  (22)
• Science: Technology: Electronics: Signal Processing  (116)

• Neural Network FAQ   - This FAQ from comp.ai.neural-nets contains the most commonly asked questions about neural networks, including some great introductory material.

• Bibliographies on Neural Networks - Part of the collection of computer science bibliographies.
• Evolutionary Design of Neural Architectures - A repository maintained by the Artificial Intelligence Research Group led by Vasant Honavar in the Department of Computer Science at Iowa State University.
• Gaussian Processes - A website keeping track of developments in Gaussian processes. Has links to online papers and their authors and software.
• Maximum Entropy Online Resources - Workshops, tutorials, papers and software related to maximum entropy.
• Neural Network Centers Around the World - Collection of Neural Network resources sorted by topic.
• Neuroinformatics - A hub for the neuroinformatics community, with information on workshops and courses. Also hosts the comp-neuro mailing list.
• Principal Curves Page - Introduction to principal curves, with summary of and links to publications, demo, and software.
• Reinforcement Learning Repository - A centralized resource for researchers of reinforcement learning. Maintained at University of Massachusetts, Amherst.
• Sumeet's neural networks listing - Includes related fields like genetic algorithms, fuzzy logic, adaptive computing and complex systems and descriptions of each site.
• Wikipedia: Neural Network - Free encyclopedia article addressing the historical background, the learning paradigms and the different application areas.

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