Armadillo is a C++ linear algebra library (matrix maths) aiming towards a good balance between speed and ease of use. Integer, floating point, and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS libraries. A delayed evaluation approach, based on template meta-programming, is used (during compile time) to combine several operations into one and reduce or eliminate the need for temporaries.
scikits.learn is a Python module that integrates classic machine learning algorithms in the tightly-knit world of scientific Python packages. It aims to provide simple and efficient solutions to learning problems that are accessible to everybody and reusable in various contexts: machine-learning as a versatile tool for science and engineering.
RecDB is a recommendation engine built entirely inside PostgreSQL 9.2. It allows application developers to build recommendation applications using a wide variety of built-in recommendation algorithms such as user-user collaborative filtering, item-item collaborative filtering, and singular value decomposition. Applications powered by RecDB can produce online and flexible personalized recommendations to end-users. It is easily used and configured and allows novice developers to define a variety of recommenders that fits their application's needs in few lines of SQL. It can seamlessly integrate recommendation functionality with traditional database operations.