An Open Source Machine Learning Framework for Everyone

An open-source Python framework for hybrid quantum-classical machine learning.

Java bindings for TensorFlow

Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors).

WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript.

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.

A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.

Models and examples built with TensorFlow

Making text a first-class citizen in TensorFlow.

Probabilistic reasoning and statistical analysis in TensorFlow