TensorFlow is an open-source machine learning framework developed by Google for building and deploying ML models across various platforms.. There are currently 14 open-source alternatives to TensorFlow, with a combined total of 38.4k GitHub stars. The most common language among these projects is Rust.
Showing 14 open-source alternatives
A Rust-based deep learning framework and tensor library optimized for flexibility, efficiency, and cross-platform portability.
A library for building and evaluating mathematical expressions and neural networks in Go, with automatic differentiation and GPU support.
An open-source machine learning framework for building classical, deep, or hybrid ML applications with a focus on performance and portability.
Multi-dimensional arrays (tensors) and numerical definitions for Elixir, enabling machine learning and scientific computing.
A Julia machine learning framework providing a unified interface and meta-algorithms for over 200 models.
An accelerated machine learning framework for Go, offering a PyTorch/Jax/TensorFlow-like experience with support for CPUs, GPUs, TPUs, and WASM.
A deep learning framework for Julia with GPU support and automatic differentiation using dynamic computational graphs.
A discontinued Python neural network framework designed for fast, flexible experimentation with CPU and GPU backends.
A collection of tutorials and resources to help developers learn JAX, Flax, and Haiku for machine learning.
A pure-Java/C# machine learning framework for neural networks, genetic programming, and classic ML algorithms with simple adaptable source code.
A standalone reimplementation of TensorFlow for Ruby, supporting pure Ruby and OpenCL backends for machine learning.
A Clojure library for dynamic neural network graphs with pluggable tensor backends, inspired by PyTorch.
A fast, flexible, and compact deep learning framework for Julia that runs on CPU and CUDA GPU.
A lightweight, platform-independent tensor library with autograd for the JVM, accelerated by OpenCL.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.