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.
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
>>> 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.
The TensorFlow project strives to abide by generally accepted best practices in open-source software development:
|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|
See TensorFlow SIG Build to find our list of community-supported TensorFlow builds.