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.
FramerD is a semi-structured object database integrated with a Scheme-based scripting language which supports multi-lingual programming (with pervasive Unicode), a stable module system for programming in the large, distributed applications (via an extensible RPC protocol), non-deterministic (PROLOG-like) evaluation for search and set operations, multi-threaded program execution, extensive tools for text and language analysis, built-in HTML/XML/MIME parsers, and intuitive (CGI- and FastCGI-based) Web scripting. The built-in object database robustly supports millions of objects and indexed access to those objects, both through disk files and networked servers.
PyStem is a fast Python module with the the Porter stemming algorithm (a process for removing the commoner morphological and inflexional endings from words in English; its main use is as part of a term normalisation process that is usually done when setting up Information Retrieval systems).