JAX
Google (Chrome DevTools team) · Training & fine-tuning
Python library for NumPy-style array computing with composable transformations (jit, grad, vmap, shard_map) compiled through XLA to CPU, GPU and TPU
8 tools
Google (Chrome DevTools team) · Training & fine-tuning
Python library for NumPy-style array computing with composable transformations (jit, grad, vmap, shard_map) compiled through XLA to CPU, GPU and TPU
The Julia Project · Programming languages & runtimes
Dynamically typed, JIT-compiled language for numerical and scientific computing that aims to combine high-level syntax with compiled-code speed
NumPy developers (NumFOCUS) · DataFrames & array computing
Foundational Python library for n-dimensional arrays, vectorized math, linear algebra, random numbers and the array API used by the scientific stack
PyTorch Foundation (Linux Foundation) · Training & fine-tuning
Open-source deep-learning framework with eager tensors, autograd, torch.compile and distributed training, governed by the PyTorch Foundation and the base of most LLM tooling
R Foundation / R Core Team · Programming languages & runtimes
Language and environment for statistical computing and graphics, with the CRAN package archive and a strong base in academic statistics and econometrics
scikit-learn developers · Mathematical & statistical computing
BSD-licensed Python machine-learning library for classification, regression, clustering, dimensionality reduction, preprocessing and model selection on NumPy and SciPy
SciPy developers (NumFOCUS) · Mathematical & statistical computing
Core open-source Python library for scientific computing on NumPy arrays: optimization, integration, interpolation, linear algebra, sparse matrices, statistics, signal processing
SymPy Development Team · Mathematical & statistical computing
Pure-Python computer algebra system for symbolic algebra, calculus, equation solving, matrices, physics modules, code generation and LaTeX output
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