Numerical Computing
Showing 27 of 27 projects
A high-level, high-performance dynamic programming language for technical computing.
A powerful Python library for data manipulation and analysis, providing fast, flexible data structures.
A Python library for composable transformations of numerical programs: automatic differentiation, vectorization, and JIT compilation to GPU/TPU.
A Python library for composable transformations of numerical programs: automatic differentiation, vectorization, and JIT compilation to GPU/TPU.
A Python library for accelerator-oriented array computation and program transformation, designed for high-performance numerical computing and machine learning.
The fundamental package for scientific computing with Python, providing powerful N-dimensional arrays and mathematical functions.
A modern C++ toolkit for machine learning, computer vision, and data analysis applications.
A comprehensive set of numeric libraries for Go, providing matrices, statistics, optimization, and graph algorithms.
An optimized open-source implementation of the Basic Linear Algebra Subprograms (BLAS) library for high-performance scientific computing.
A library for building and evaluating mathematical expressions and neural networks in Go, with automatic differentiation and GPU support.
A standard library for JavaScript and TypeScript with an emphasis on numerical and scientific computation.
A fast, header-only C++ machine learning library with bindings for Python, R, Julia, and Go.
Rust language bindings for TensorFlow, providing idiomatic access to machine learning capabilities.
A templatized header-only C++ implementation of the Python NumPy library for numerical computing.
A C++ library for numerical analysis with multi-dimensional array expressions featuring broadcasting and lazy computing.
An open-source numerical library for .NET and Mono providing algorithms for scientific computing, linear algebra, statistics, and more.
A lightweight, dependency-free JavaScript library for descriptive, regression, and inference statistics.
A numerical processing library for Scala, providing generic, clean, and powerful linear algebra and scientific computing capabilities.
Multi-dimensional arrays (tensors) and numerical definitions for Elixir, enabling machine learning and scientific computing.
A portable software framework for instantiating high-performance BLAS-like dense linear algebra libraries.
A pure Rust linear algebra library focusing on portability, correctness, and performance with both low-level routines and high-level wrappers.
A gradient processing and optimization library for JAX, designed for research with composable building blocks.
A PHP library for arbitrary-precision arithmetic with support for integers, decimals, and rational numbers.
A C++17 library for automatic differentiation with forward and reverse mode support, enabling efficient derivative computation.
A portable mixed-precision math library with 2,000+ SIMD kernels for 15+ numeric types across x86, Arm, RISC-V, and WebAssembly.
A neural network library for Elixir built on Nx, providing functional, model creation, and training APIs for deep learning.
A portable C++ library providing SIMD vector types for explicit data-parallel programming with zero-overhead abstractions.
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