TensorFlow

2015 Google Releases TensorFlow

“TensorFlow is an open source library that was created by Google. It is used to design, build, and train deep learning models.” An Open Source Machine Learning Framework for Everyone https://tensorflow.org

Fair Use Source: https://github.com/topics/tensorflow

TensorFlow
TensorFlow

https://github.com/topics/tensorflow

Created by Google Brain Team

Released November 9, 2015

GitHub: tensorflow

Official Website: www.tensorflow.org

Wikipedia

Related Topics

Deep Learning – on GitHub: deep-learning

Datasets – on GitHub: dataset

Machine Learning – on GitHub: machine-learning

See also AI Glossary, AI Bibliography

Google’s machine learning framework.

TensorFlow is a free and open-source software library for dataflow and differentiable programming across a range of tasks. It is a symbolic math library, and is also used for machine learning applications such as neural networks. It is used for both research and production at Google. TensorFlow was developed by the Google Brain team for internal Google use. It was released under the Apache License 2.0 on November 9, 2015.” Fair Use Source: https://en.wikipedia.org/wiki/TensorFlow

Documentation

TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of toolslibraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.

TensorFlow was originally developed by researchers and engineers working on the Google Brain team within Google’s Machine Intelligence Research organization to conduct machine learning and deep neural networks research. The system is general enough to be applicable in a wide variety of other domains, as well.

TensorFlow provides stable Python and C++ APIs, as well as non-guaranteed backward compatible API for other languages.

Keep up-to-date with release announcements and security updates by subscribing to announce@tensorflow.org. See all the mailing lists.

Install

See the TensorFlow install guide for the pip package, to enable GPU support, use a Docker container, and build from source.

To install the current release, which includes support for CUDA-enabled GPU cards (Ubuntu and Windows):

$ pip install tensorflow

A smaller CPU-only package is also available:

$ pip install tensorflow-cpu

To update TensorFlow to the latest version, add --upgrade flag to the above commands.

Nightly binaries are available for testing using the tf-nightly and tf-nightly-cpu packages on PyPi.

Try your first TensorFlow program

$ python
>>> import tensorflow as tf
>>> tf.add(1, 2).numpy()
3
>>> hello = tf.constant('Hello, TensorFlow!')
>>> hello.numpy()
'Hello, TensorFlow!'

For more examples, see the TensorFlow tutorials.

Contribution guidelines

If you want to contribute to TensorFlow, be sure to review the contribution guidelines. This project adheres to TensorFlow’s code of conduct. By participating, you are expected to uphold this code.

We use GitHub issues for tracking requests and bugs, please see TensorFlow Discuss for general questions and discussion, and please direct specific questions to Stack Overflow.

The TensorFlow project strives to abide by generally accepted best practices in open-source software development:

CII Best Practices
Contributor Covenant

Continuous build status

Official Builds

Build TypeStatusArtifacts
Linux CPUPyPI
Linux GPUPyPI
Linux XLATBA
macOSPyPI
Windows CPUPyPI
Windows GPUPyPI
Android
Raspberry Pi 0 and 1 Py2 Py3
Raspberry Pi 2 and 3 Py2 Py3

Community Supported Builds

Build TypeStatusArtifacts
Linux AMD ROCm GPU NightlyNightly
Linux AMD ROCm GPU Stable ReleaseRelease 1.15 / 2.x
Linux s390x NightlyNightly
Linux s390x CPU Stable ReleaseRelease
Linux ppc64le CPU NightlyNightly
Linux ppc64le CPU Stable ReleaseRelease 1.15 / 2.x
Linux ppc64le GPU NightlyNightly
Linux ppc64le GPU Stable ReleaseRelease 1.15 / 2.x
Linux CPU with Intel® MKL-DNN NightlyNightly
Linux CPU with Intel® MKL-DNN Stable ReleaseRelease 1.15 / 2.x
Red Hat® Enterprise Linux® 7.6 CPU & GPU
Python 2.7, 3.6
1.13.1 PyPI

Resources

Learn more about the TensorFlow community and how to contribute.

License

Apache License 2.0

Fair Use Source: https://github.com/tensorflow/tensorflow

WrongThink

See also Privacy vs Surveillance Topics, Big Brother, 1984

Contrast with WrongThink. The New GroupThink is what must be followed if you do not want to be censored and shadow banned by the corporate Silicon Valley Surveillance State made up Facebook, Twitter, and Google the Googlag (Google as Big Brother).

Googlag

See Google. See also Privacy vs Surveillance Topics.

The Surveillance State is Facebook, Twitter and Google the Googlag (Google as Big Brother). They actively censor and shadow ban anyone who does not follow the New GroupThink. This censorship is referred to as “being sent to the Googlag” (Gulag).

GroupThink

See also Privacy vs Surveillance Topics, Big Brother, 1984

Contrast with WrongThink. The New GroupThink is what must be followed if you do not want to be censored and shadow banned by the corporate Silicon Valley Surveillance State made up Facebook, Twitter, and Google the Googlag (Google as Big Brother).