TensorFlow is an open-source project. This page explains how to contribute, where to ask questions, and how to help each other.
The source code for TensorFlow is on GitHub.
Before contributing to TensorFlow source code, please review the Contribution guidelines.
Projects developed by the TensorFlow community
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
- Caffe to TensorFlow model converter
- Bitfusion's` GPU-enabled AWS EC2 TensorFlow AMI (Launch AMI)
- Rust language bindings
- Operator Vectorization Library
- Swift language bindings
- Sublime Tensorflow - A plugin for Sublime Text
- Edward - A library for probabilistic modeling, inference, and criticism (Github, Forum)
- GPflow - Gaussian processes in TensorFlow
- CS 20SI: Tensorflow for Deep Learning Research - Please note, this course was designed with TensorFlow v0.12, so some of the notes may be out of date - but it's still a great resource.
TensorFlow Communities Around the World
- TensorFlow Korea (TF-KR) User Group (Korean language)
- TensorFlow User Group Tokyo (Japanese Language)
- Soleil Data Dojo (Japanese language)
- TensorFlow User Group Utsunomiya
TensorFlow provides multiple communication paths. To pick the right path, please read the following list carefully:
- To ask or answer technical questions about TensorFlow, use Stack Overflow. For example, ask or search Stack Overflow about a particular error message you encountered during installation.
- To join general discussions about TensorFlow development and directions, please join the TensorFlow discuss mailing list. For example, use this mailing list to learn about new features in upcoming releases of TensorFlow.
- To report bugs or make feature requests, use the TensorFlow issues tracker on GitHub. For example, use the issue tracker to request a new operation in TensorFlow.