SHOGUN is a machine learning toolbox whose focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It provides a generic SVM object interfacing to several different SVM implementations, all making use of the same underlying, efficient kernel implementations. Apart from SVMs and regression, SHOGUN also features a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons, and algorithms to train hidden Markov models. SHOGUN can be used from within C++, Matlab, R, Octave, and Python.
Fast Artificial Neural Network Library is a neural network library that implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported. It includes a framework for easy handling of training data sets. It is easy to use, versatile, well documented, and fast. C++, Perl, PHP, .NET, Python, Delphi, Octave, Pure Data, and Mathematica bindings are available. A reference manual accompanies the library with examples and recommendations on how to use the library. A graphical user interface is also available for the library.
Presage (formerly known as Soothsayer) is an intelligent predictive text entry platform. It exploits redundant information embedded in natural languages to generate predictions. Its modular and pluggable architecture allows its language model to be extended and customized to utilize statistical, syntactic, and semantic information sources.
Narval is a framework dedicated to the setting up of intelligent personal assistants (IPAs). It includes a language, an interpreter, and a GUI/IDE. It is based on artificial intelligence and agent technologies. It executes recipes (sequences of actions) to perform tasks. It is easy to specify new actions using XML and to implement them using Python. Recipes can be constructed graphically (without programming) by linking blocks representing the actions.
MyMediaLite is a lightweight, multi-purpose library of recommender system algorithms. It addresses the two most common scenarios in collaborative filtering: rating prediction (e.g. on a scale of 1 to 5 stars), and item prediction from implicit feedback (e.g. from clicks or purchase actions). It contains dozens of recommender engines, including state-of-the-art matrix factorization methods. It also supports real-time updates to the recommender engines, storing engines to disk and reloading them again, and several evaluation measures to compare the accuracy of different recommender system methods. Three command-line programs that offer most of the functionality contained in the library are included.
Howie is an artificial intelligence agent with a natural language interface (a "chatterbot"). It is designed to be simple to install, configure, and extend. The emphasis is less on simulating a human conversation, and more on providing a "virtual assistant" which provides useful services to visitors through a natural, conversational interface.
RebeccaAIML is an enterprise cross platform AIML development platform. RebeccaAIML supports C++, Java, C#, Python, and many other programming languages. It allows AIML development out of the box. RebeccaAIML also comes with an array of AIML administration tools, great documentation, and an Eclipse AIML editor plugin.