PyTorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

•    Python

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PyTorch is a deep learning framework that puts Python first. It is a python package that provides Tensor computation (like numpy) with strong GPU acceleration, Deep Neural Networks built on a tape-based autograd system. You can reuse your favorite python packages such as numpy, scipy and Cython to extend PyTorch when needed.

neural-network autograd gpu numpy deep-learning tensor

pytorch-book - PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation

•    Jupyter

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PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation

pytorch pytorch-tutorials pytorch-tutorials-cn deep-learning neural-style charrnn gan caption neuraltalk image-classification visdom tensorboard nn tensor autograd jupyter-notebook

flashlight - A C++ standalone library for machine learning

•    C++

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First, build and install Flashlight and link it to your own project.

machine-learning deep-learning neural-network cpp ml autograd flashlight

owl - Owl is an OCaml library for scientific and engineering computing.

•    OCaml

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Owl 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-network

awesome-jax - JAX - A curated list of resources https://github.com/google/jax

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JAX brings automatic differentiation and the XLA compiler together through a NumPy-like API for high performance machine learning research on accelerators like GPUs and TPUs. This section contains libraries that are well-made and useful, but have not necessarily been battle-tested by a large userbase yet.

machine-learning awesome deep-learning neural-network numpy autograd awesome-list jax xla

Arraymancer - A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU, OpenCL and embedded devices

•    Nim

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Arraymancer 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 autograd

scorch - scorch is a deep learning framework in Scala inspired by PyTorch

•    Scala

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Scorch is a deep learning framework in Scala inspired by PyTorch. It has automatic differentiation built in and follows an imperative coding style.

deep-learning pytorch autograd

flint - A toy deep learning framework implemented in pure Numpy from scratch

•    Python

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A toy deep learning framework implemented in Numpy from scratch with a PyTorch-like API. I'm trying to make it as clean as possible. Flint is not as powerful as torch, but it is still able to start a fire.

deep-learning neural-network numpy autograd autodiff autodifferentiation