arovir01/tensorflow

`Documentation`

TensorFlow is an end-to-end open source platform
for machine learning. It has a comprehensive, flexible ecosystem of
tools,
libraries, 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()
b'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:

Continuous build status

You can find more community-supported platforms and configurations in the
TensorFlow SIG Build community builds table.

Official Builds

Build Type	Status	Artifacts
Linux CPU		PyPI
Linux GPU		PyPI
Linux XLA		TBA
macOS		PyPI
Windows CPU		PyPI
Windows GPU		PyPI
Android		Download
Raspberry Pi 0 and 1		Py3
Raspberry Pi 2 and 3		Py3
Libtensorflow MacOS CPU	Status Temporarily Unavailable	Nightly Binary Official GCS
Libtensorflow Linux CPU	Status Temporarily Unavailable	Nightly Binary Official GCS
Libtensorflow Linux GPU	Status Temporarily Unavailable	Nightly Binary Official GCS
Libtensorflow Windows CPU	Status Temporarily Unavailable	Nightly Binary Official GCS
Libtensorflow Windows GPU	Status Temporarily Unavailable	Nightly Binary Official GCS