Tensors and Dynamic neural networks in Python with strong GPU acceleration

PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)

Open deep learning compiler stack for cpu, gpu and specialized accelerators

NumPy & SciPy for GPU

Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.

Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

MegEngine 是一个快速、可拓展、易于使用且支持自动求导的深度学习框架

LibRec: A Leading Java Library for Recommender Systems, see

Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.

Multi-dimensional arrays (tensors) and numerical definitions for Elixir

C++ DataFrame for statistical, Financial, and ML analysis -- in modern C++ using native types and contiguous memory storage

A list of awesome compiler projects and papers for tensor computation and deep learning.

On-device AI across mobile, embedded and edge for PyTorch

Inference Llama 2 in one file of pure 🔥

2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

Deep learning in Rust, with shape checked tensors and neural networks

TensorLy: Tensor Learning in Python.

A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends

The Tensor Algebra Compiler (taco) computes sparse tensor expressions on CPUs and GPUs

common in-memory tensor structure