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Armadillo: fast C++ library for linear algebra & scientific computing - http://arma.sourceforge.net

https://github.com/conradsnicta/armadillo-code

Neanderthal is a Clojure library for fast matrix and linear algebra computations based on the highly optimized native libraries of BLAS and LAPACK computation routines for both CPU and GPU.. Read the documentation at Neanderthal Web Site.

clojure-library matrix gpu gpu-computing gpgpu opencl cuda high-performance-computing vectorization api matrix-factorization matrix-multiplication matrix-functions matrix-calculationsOwl is an emerging numerical library for scientific computing and engineering. The library is developed in the OCaml language and inherits all its powerful features such as static type checking, powerful module system, and superior runtime efficiency. Owl allows you to write succinct type-safe numerical applications in functional language without sacrificing performance, significantly reduces the cost from prototype to production use. Owl's documentation contains a lot of learning materials to help you start. The full documentation consists of two parts: Tutorial Book and API Reference. Both are perfectly synchronised with the code in the repository by the automatic building system. You can access both parts with the following link.

matrix linear-algebra ndarray statistical-functions topic-modeling regression maths gsl plotting sparse-linear-systems scientific-computing numerical-calculations statistics mcmc optimization autograd algorithmic-differentation automatic-differentiation machine-learning neural-networkArmadillo is a fast, template based, C++ matrix library with optional interface to LAPACK and ATLAS libraries, including high-performance versions such as Intel MKL and AMD ACML. Integer, floating point and complex numbers are supported, as well as disk storage and a subset of trigonometric and statistics functions. Armadillo has an easy to use syntax, deliberately similar to Matlab. For more details, see http://arma.sourceforge.net

A high performance linear algebra library, written in JavaScript and optimized with C++ bindings to BLAS. The documentation is located in the wiki section of this repository.

blas matrix vector linear-algebra high-performance-computing machine-learning linear algebraBLIS is a portable software framework for instantiating high-performance BLAS-like dense linear algebra libraries. The framework was designed to isolate essential kernels of computation that, when optimized, immediately enable optimized implementations of most of its commonly used and computationally intensive operations. BLIS is written in ISO C99 and available under a new/modified/3-clause BSD license. While BLIS exports a new BLAS-like API, it also includes a BLAS compatibility layer which gives application developers access to BLIS implementations via traditional BLAS routine calls. An object-based API unique to BLIS is also available. For a thorough presentation of our framework, please read our journal article, "BLIS: A Framework for Rapidly Instantiating BLAS Functionality". For those who just want an executive summary, please see the next section.

blis blas linear-algebra linear-algebra-library matrix-multiplication matrix-calculations matrix-libraryArraymancer is a tensor (N-dimensional array) project in Nim. The main focus is providing a fast and ergonomic CPU, Cuda and OpenCL ndarray library on which to build a scientific computing and in particular a deep learning ecosystem. The library is inspired by Numpy and PyTorch. The library provides ergonomics very similar to Numpy, Julia and Matlab but is fully parallel and significantly faster than those libraries. It is also faster than C-based Torch.

tensor nim multidimensional-arrays cuda deep-learning machine-learning cudnn high-performance-computing gpu-computing matrix-library neural-networks parallel-computing openmp linear-algebra ndarray opencl gpgpu iot automatic-differentiation autogradEigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms. It supports all matrix sizes, from small fixed-size matrices to arbitrarily large dense matrices, and even sparse matrices. It supports all standard numeric types, including std::complex, integers, and is easily extensible to custom numeric types. It also supports various matrix decompositions and geometry features.

linear-algebra vectors geomentry matrix algorithmGosl is a Go library to develop Artificial Intelligence and High-Performance Scientific Computations. The library tries to be as general and easy as possible. Gosl considers the use of both Go concurrency routines and parallel computing using the message passing interface (MPI). Gosl has several modules (sub-packages) for a variety of tasks in scientific computing, image analysis, and data post-processing.

scientific-computing visualization linear-algebra differential-equations sparse-systems plotting mkl parallel-computations computational-geometry graph-theory tensor-algebra fast-fourier-transform eigenvalues eigenvectors hacktoberfest machine-learning artificial-intelligence optimization optimization-algorithms linear-programmingRumale (Ruby machine learning) is a machine learning library in Ruby. Rumale provides machine learning algorithms with interfaces similar to Scikit-Learn in Python. Rumale supports Linear / Kernel Support Vector Machine, Logistic Regression, Linear Regression, Ridge, Lasso, Kernel Ridge, Factorization Machine, Naive Bayes, Decision Tree, AdaBoost, Gradient Tree Boosting, Random Forest, Extra-Trees, K-nearest neighbor classifier, K-Means, K-Medoids, Gaussian Mixture Model, DBSCAN, SNN, Power Iteration Clustering, Mutidimensional Scaling, t-SNE, Principal Component Analysis, Kernel PCA and Non-negative Matrix Factorization. This project was formerly known as "SVMKit". If you are using SVMKit, please install Rumale and replace SVMKit constants with Rumale.

machine-learning data-science data-analysis artificial-intelligenceSciRust is a Scientific computing library written in Rust programming language. The objective is to design a generic library which can be used as a backbone for scientific computing. Its current areas of focus includes Matrices, Linear algebra, Statistics, and Signal processing.

scientific computing algebra matrixVexCL is a vector expression template library for OpenCL/CUDA. It has been created for ease of GPGPU development with C++. VexCL strives to reduce amount of boilerplate code needed to develop GPGPU applications. The library provides convenient and intuitive notation for vector arithmetic, reduction, sparse matrix-vector products, etc. Multi-device and even multi-platform computations are supported. The source code of the library is distributed under very permissive MIT license.

opencl cuda c-plus-plus gpgpu scientific-computing cpp11The Accord.NET project provides machine learning, statistics, artificial intelligence, computer vision and image processing methods to .NET. It can be used on Microsoft Windows, Xamarin, Unity3D, Windows Store applications, Linux or mobile.

machine-learning framework c-sharp nuget visual-studio statistics unity3d neural-network support-vector-machines computer-vision image-processing ffmpegThe GNU Scientific Library (GSL) is a numerical library for C and C++ programmers. The library provides a wide range of mathematical routines such as random number generators, special functions and least-squares fitting. There are over 1000 functions in total with an extensive test suite.

math mathematics numerical scientific algorithms random-numberA linear algebra and mathematics library for computer graphics. Not all of the functionality has been implemented yet, and the existing code is not fully covered by the testsuite. If you encounter any mistakes or omissions please let me know by posting an issue, or even better: send me a pull request with a fix.

linear-algebra matrix vector computer-graphics simd simd-vector mathematics-libraryA purely functional interface to linear algebra and other numerical algorithms, internally implemented using LAPACK, BLAS, GSL and SUNDIALS. This package includes matrix decompositions (eigensystems, singular values, Cholesky, QR, etc.), linear solvers, numeric integration, root finding, etc.

dlib is a library for developing portable applications dealing with networking, threads, graphical interfaces, data structures, linear algebra, machine learning, XML and text parsing, numerical optimization, Bayesian nets, data compression routines, linked lists, binary search trees, linear algebra and matrix utilities, machine learning algorithms, and many other general utilities.

cpp-utilities-library library algorithms compression thread bayesian machine-learning xml-parserLow-Rank and Sparse tools for Background Modeling and Subtraction in Videos. The LRSLibrary provides a collection of low-rank and sparse decomposition algorithms in MATLAB. The library was designed for motion segmentation in videos, but it can be also used (or adapted) for other computer vision problems (for more information, please see this page). Currently the LRSLibrary offers more than 100 algorithms based on matrix and tensor methods. The LRSLibrary was tested successfully in several MATLAB versions (e.g. R2014, R2015, R2016, R2017, on both x86 and x64 versions). It requires minimum R2014b.

rpca matrix-factorization matrix-completion tensor-decomposition tensor matlab matrix subspace-tracking subspace-learningLinear algebra library for the Rust programming language.

linear-algebra matrix vector algebraLinear algebra library for the Rust programming language.

linear-algebra matrix vector algebraThe Universal Java Matrix Package (UJMP) is a Java library which provides implementations for sparse and dense matrices, as well as linear algebra calculations such as matrix decomposition, inverse, multiply, mean, correlation, standard deviation, etc.

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