Additional details about the TensorFlow programming model and the underlying implementation can be found in this paper:
The original white paper introducing TensorFlow can be found here:
A white paper about contrib.learn is also available:
If you use TensorFlow in your research and would like to cite the TensorFlow system, we suggest you cite the paper above. You can use this BibTeX entry. As the project progresses, we may update the suggested citation with new papers.
Please only use the TensorFlow name and marks when accurately referencing this software distribution, and do not use our marks in a way that suggests you are endorsed by or otherwise affiliated with Google. When referring to our marks, please include the following attribution statement: "TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc."
TensorFlow enables researchers to build machine learning models. We collect such models in our Zoo. If you have built a model with TensorFlow, you may consider publishing it there.
We keep a list of projects that use TensorFlow here. If you made something amazing with TensorFlow, we'd like to hear about it!
The TensorFlow community has created many great projects around TensorFlow, including:
- Machine Learning with TensorFlow (Book & Code)
- @jtoy's awesome "Awesome TensorFlow" list of awesome things
- TensorFlow tutorials
- Scikit Flow - Simplified Interface for TensorFlow
- Caffe to TensorFlow model converter
- Bitfusion's` GPU-enabled AWS EC2 TensorFlow AMI (Launch AMI)
- Rust language bindings
- Operator Vectorization Library
The source code for TensorFlow is hosted on GitHub: https://github.com/tensorflow/tensorflow.
If you are interested in contributing to TensorFlow please review the contributing guide.
For help and support, technical or algorithmic questions, please submit your questions to Stack Overflow: https://stackoverflow.com/questions/tagged/tensorflow. You may also find answers in our FAQ, our glossary, or in the shapes, sizes and types guide. Please do not use the mailing list or issue tracker for support.
For general discussions, please join the TensorFlow discuss mailing list. This list is intended for general discussions about TensorFlow development and directions, not as a help forum. Instead, direct your questions to Stack Overflow, and report issues on GitHub.
Please report bugs, feature requests and installation / compatibility issues on the TensorFlow issues tracker on GitHub. If you need help with using TensorFlow, please do not use the issue tracker for that. Instead, direct your questions to Stack Overflow.
TensorFlow uses Semantic Versioning 2.0. For details on the versioning of our public API and binary compatibility, see the versioning document. Additional details for developers are in TensorFlow Data Versioning.
A roadmap containing what we're working on at the moment is here.