Skip to content

Computation using data flow graphs for scalable machine learning

License

Notifications You must be signed in to change notification settings

rthouvenin/tensorflow

 
 

Repository files navigation

#TensorFlow

Linux CPU Build Status Linux GPU PIP Build Status Mac OS CPU Build Status Android Build Status

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture lets you deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device without rewriting code. TensorFlow was originally developed by researchers and engineers working on the Google Brain team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research. The system is general enough to be applicable in a wide variety of other domains, as well.

If you'd like to contribute to tensorflow, be sure to review the contribution guidelines.

We use github issues for tracking requests and bugs, but please see Community for general questions and discussion.

Download and Setup

See install instructions.

Try your first TensorFlow program

$ python

>>> import tensorflow as tf
>>> hello = tf.constant('Hello, TensorFlow!')
>>> sess = tf.Session()
>>> sess.run(hello)
Hello, TensorFlow!
>>> a = tf.constant(10)
>>> b = tf.constant(32)
>>> sess.run(a+b)
42
>>>

##For more information

About

Computation using data flow graphs for scalable machine learning

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • C++ 53.7%
  • Python 28.9%
  • Jupyter Notebook 6.6%
  • HTML 5.8%
  • TypeScript 2.5%
  • C 1.3%
  • Other 1.2%