About: Armadillo is a high quality C++ library for linear algebra & scientific computing, aiming towards a good balance between speed and ease of use. The function syntax is deliberately similar to MATLAB. Useful for algorithm development directly in C++, or quick conversion of research code into production environments (eg. software & hardware products).

• faster handling of sparse matrices by kron() and repmat()
• faster transpose of sparse matrices
• faster element access in sparse matrices
• faster row iterators for sparse matrices
• faster handling of compound expressions by trace()
• more efficient handling of aliasing in submatrix views
• expanded normalise() to handle sparse matrices
• expanded .transform() and .for_each() to handle sparse matrices
• added reverse() for reversing order of elements
• added repelem() for replicating elements
• added roots() for finding the roots of a polynomial

About: MLweb is an open source project that aims at bringing machine learning capabilities into web pages and web applications, while maintaining all computations on the client side. It includes (i) a javascript library to enable scientific computing within web pages, (ii) a javascript library implementing machine learning algorithms for classification, regression, clustering and dimensionality reduction, (iii) a web application providing a matlab-like development environment.

• Add bibtex entry of corresponding Neurocomputing paper
• Create javascript modules to avoid global scope pollution in web pages

About: The Universal Java Matrix Package (UJMP) is a data processing tool for Java. Unlike JAMA and Colt, it supports multi-threading and is therefore much faster on current hardware. It does not only support matrices with double values, but instead handles every type of data as a matrix through a common interface, e.g. CSV files, Excel files, images, WAVE audio files, tables in SQL data bases, and much more.

Updated to version 0.3.0

About: FsAlg is a linear algebra library that supports generic types.

Initial Announcement on mloss.org.

About: jblas is a fast linear algebra library for Java. jblas is based on BLAS and LAPACK, the de-facto industry standard for matrix computations, and uses state-of-the-art implementations like ATLAS for all its computational routines, making jBLAS very fast.

Changes from 1.0:

• Added singular value decomposition
• Fixed bug with returning complex values
• Many other minor improvements