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The Dambach Linear Algebra Framework is a general purpose Linear Algebra framework for .Net. The main goal is to enable ordinary programmers (who do not have a math degree) to make use of linear algebra methods in solving everyday problems.

http://linearalgebra.codeplex.com/Tags | algebra garbage linear linear-algebra linear-systems math matrices |

Implementation | |

License | BSD |

Platform | Windows |

A library for basic linear algebra operations. It requires linearMatrix

C++ implementation for matrices, vectors, and other linear algebra.

Basic linear algebra for small matrices in C

Template library for linear algebra: vectors, matrices, and related algorithms

Implementations of selected sparse matrix formats for linear algebra supporting scientific and machine learning applications.Machine learning applications typically model entities as vectors of numerical features so that they may be compared and analysed quantitively. Typically the majority of the elements in these vectors are zeros. In the case of text mining applications, each document within a corpus is represented as a vector and its features represent the vocabulary of unique words. A corpus of several thousand documents might utilise a vocabulary of hundreds of thousands (or perhaps even millions) of unique words but each document will typically only contain a couple of hundred unique words. This means the number of non-zero values in the matrix might only be around 1%.

matrix scientific-computing machine-learning sparse-matrices matrices csr coo csc dictionary-of-keysJLinAlg is a Java Library for Linear Algebra without rounding errors ( e.g. operations on matrices, algorithms for solving Linear Equation Systems, inverting matrices, computing the determinant or the eigenvalues of a matrix).

Basic math classes, Linear Algebra, probabilities, etc..

C# Math Library, focused in linear algebra tools

A linear algebra framework in C++ along with a layout abstraction for parallelization paradigms. It provides operators to compute dense and sparse matrices with generically designed scalar, complex, vector and matrix types. At this time, the framework supports the libraries CUDA, CUBLAS, CUSP, CUSPARSE for parallel computing on GPGPU.

LAPACK++ is a library for high performance linear algebra computations. This version includes support for solving linear systems using LU, Cholesky, QR matrix factorizations, for real and complex matrices.

A cool library for easily managing matrices, vectors, linear systems, and other linear algebra structures

A cool library for easily managing matrices, vectors, linear systems, and other linear algebra structures

Talk for Scala eXchange 2014: High Performance Linear Algebra in Scala

An IBL-style linear algebra set of notes

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