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:PyPI Linux GPU PyPI Linux XLA TBA macOS PyPI Windows CPU PyPI Windows GPU PyPI Android Raspberry Pi 0 and 1 Py3 Raspberry Pi 2 and 3 Py3 Libtensorflow MacOS CPU GCS Libtensorflow Linux CPU GCS Libtensorflow Linux GPU GCS Libtensorflow Windows CPU GCS Libtensorflow Windows GPU GCS Nightly Linux AMD ROCm GPU Stable Release Release 1.15 / 2.x Linux s390x Nightly Nightly Linux s390x CPU Stable Release Release Linux ppc64le CPU Nightly Nightly Linux ppc64le CPU Stable Release Release 1.15 / 2.x Linux ppc64le GPU Nightly Nightly Linux ppc64le GPU Stable Release Release 1.15 / 2.x Linux CPU with Intel oneAPI Deep Neural Network Library (oneDNN) Nightly Nightly Linux CPU with Intel oneAPI Deep Neural Network Library (oneDNN) Stable Release Release 1.15 / 2.x Red Hat® Enterprise Linux® 7.6 CPU & GPU
Copy the snippet above into CLI.