30 open-source projects similar to jackmott/simdarray, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best SIMDArray alternative.
This repository serves as an educational collection of interactive notebooks and code examples designed to demonstrate fundamental machine learning and deep learning concepts. It provides a structured environment for exploring data science workflows, ranging from basic numerical computing and statistical analysis to the construction of complex neural network architectures. The project distinguishes itself through a focus on hands-on experimentation, offering practical implementations for tasks such as computer vision, natural language processing, and statistical simulation. Users can engage w
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
Linear algebra, eigenvalues, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne twister, probability distributions, optimisation, differential equations.
This repo contains the curated FsLab stack and acts as a public discussion board for all things FsLab.
| Build status | Linux | macOS | Windows | | --- | --- | ----------- | --- | | .NET Framework / Mono | | | | | .NET Core (experimental) | | | |
Gonum is a numerical computing library for the Go programming language, providing a collection of packages for scientific computing, linear algebra, statistics, and optimization. It functions as a framework for performing complex numerical computations and solving systems of linear equations. The project includes a dedicated graph analysis framework for modeling network graphs and solving connectivity and pathfinding problems. It also provides a statistical analysis toolkit for computing descriptive and inferential statistics and estimating mixture entropy. The library's capability surface c
This project is a numerical computing library designed for scientific and engineering mathematical operations. It functions as a comprehensive linear algebra framework, a statistical analysis library, and a toolkit for mathematical optimization and numerical integration. The library is distinguished by its provider-based native acceleration, which allows managed code to be swapped for platform-native binary libraries to increase the performance of computationally intensive routines. It also supports a hybrid approach to matrix storage, implementing separate strategies for dense and sparse mat
A well tested and comprehensive Golang statistics library package with no dependencies.
A group of neural-network libraries for functional and mainstream languages
Types and utilities for working with 2d geometry in Golang
DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration