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A system that shall predict good days and locations for cross country free flying such as paragliding by comparing current weather predictions with statistics about past weather predictions and flights from online contests.
The Mars Rover Simulator project is based on the evolutionary robotics paradigm where an artificial agent acquires its skills through the process of artificial evolution. This simulator can be useful to evolve neural network controllers for the rover
Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.
Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
Cougar Squared is a new Java library for machinelearning and data mining research, supporting research needs of the community. It is written by researchers for researchers. It extends the WEKA and YALE machinelearning frameworks.
The Python Computer Vision Framework is an opened project deisgned for all those interested in computer vision. It aims at making computer vision more easy and structured and matlab-free.
It may also be used for other artistic and scientific areas.
Feating constructs a classification ensemble comprising a set of local models. It is effective at reducing the error of both stable and unstable learners, including SVM. For details see the paper at http://dx.doi.org/10.1007/s10994-010-5224-5.
Leark is a Data Mining library developed in C#.NET. It contains several methods for ranking web documents described with a set of normalized features, and a feature selection algorithm. The methods are based on perceptron and clustering.
RoboBeans is an interface to the "Robocup 2D Soccer Simulation Server" that allows developers to write Robocup teams\agents concentrating on behaviour and AI without having to worry about syntax of communication or network issues.
Torch5 provides a matlab-like environment for state-of-the-art machinelearning algorithms. It is easy to use and provides a very efficient implementation, thanks to a easy and fast scripting language (Lua) and a underlying C++ implementation.
The data complexity library, DCoL, is a machinelearning software that implements all metrics to characterize the apparent complexity of classification problems. The code is implemented in C++ and can be run on multiple platforms.
SURIKATA (Syntactic Universal Reasoning for Inducing Kolmogorov Abstract Theories Automatically) is a system for searching large spaces of artifacts and inducing algorithms for generating similar artifacts.
The aim of ALIVE is to develop new approaches to the engineering of flexible, adaptable distributed service-oriented systems based on the adaptation of social coordination and organisation mechanisms.
Content Addressable Memory, Multi-Variate Statistics, Data Mining Includes analyzing datasets, extracting patterns, creating empirical expert system. Computes joint probabilities and implements a "belief" as the solution of an equilibrium equation
Parallel Reinforcement Evolutionary Artificial Neural Networks (PREANN) is a framework of flexible multi-layer ANN's with reinforcement learning based on genetic algorithms and a parallel implementation (using XMM registers and NVIDIA's CUDA).
KeplerWeka adds the functionality of the open-source machinelearning and data mining workbench WEKA to the free and open-source, scientific workflow application, Kepler.
Yann is Yet Another Neural Network. Yann is a library to create fast neural networks. It is also a GUI to easily create, edit, train, execute and investigate networks. Multiple topologies, runtime properties and ensemble learning are supported.
Onyx is for rapid prototyping and large-scale experimentation on advanced machine-learning algorithms with an emphasis on algorithms for online or streaming analysis, modeling, and classification.
CrfAny is a C++ package for efficient and exact training and inference of Conditional Random Fields over any graphical structure, supporting all feature types (boolean, integer and real) and command line, C++/Python Lib interfaces.
The Naval Postgraduate School MachineLearning Library. There are no official releases yet, but you can pull from the mercurial repository. See the wiki for help: https://sourceforge.net/apps/mediawiki/npsml/index.php?title=Main_Page
SAIM allows to interlink knowledge bases in the Semantic Web. It focuses on instance matching of very large knowledge bases available as SPARQL endpoints. SAIM uses machinelearning techniques and is compatible with SILK.