TensorFlow is an open-source framework for machine learning created by Google. It supports deep-learning and general numerical computations on CPUs, GPUs, and clusters of GPUs. It is subject to the terms and conditions of the Apache License 2.0.

Databricks Runtime for Machine Learning, includes TensorFlow and TensorBoard, so you can use these libraries without installing any packages. For the version of TensorFlow installed in the Databricks Runtime ML version that you are using, see the release notes.


This guide is not a comprehensive guide on TensorFlow. See the TensorFlow website.

Single node and distributed training

To test and migrate single-machine workflows, use a Single Node cluster.

For distributed training options for deep learning, see Distributed training.

Example notebook

The following notebook shows how you can run TensorFlow (1.x and 2.x) with TensorBoard monitoring on a Single Node cluster.

TensorFlow 1.15/2.x notebook

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