Explore libraries to build advanced models or methods using TensorFlow, and access domain-specific application packages that extend TensorFlow.
The TensorFlow Model Optimization Toolkit is a suite of tools for optimizing ML models for deployment and execution.
Tensor2Tensor is a library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
A Python library that includes implementations of TensorFlow optimizers for training machine learning models with differential privacy.
TRFL (pronounced “truffle”) is a library for reinforcement learning building blocks created by DeepMind.
A language for distributed deep learning, capable of specifying a broad class of distributed tensor computations.
Makes it easy to store and manipulate data with non-uniform shape, including text (words, sentences, characters), and batches of variable length.
Magenta is a research project exploring the role of machine learning in the process of creating art and music.
Nucleus is a library of Python and C++ code designed to make it easy to read, write and analyze data in common genomics file formats like SAM and VCF.
A learning framework to train neural networks by leveraging structured signals in addition to feature inputs.