Databricks Runtime 4.1 ML (EoS)
Note
Support for this Databricks Runtime version has ended. For the end-of-support date, see End-of-support history. For all supported Databricks Runtime versions, see Databricks Runtime release notes versions and compatibility.
Databricks Runtime 4.1 ML provides a ready-to-go environment for machine learning and data science. It contains multiple popular libraries, including TensorFlow, Keras, and XGBoost. It also supports distributed TensorFlow training using Horovod.
Note
This release was deprecated on January 17, 2019. We recommend that you use a newer version of Databricks Runtime ML, depending on which library versions you want to use.
For more information, including instructions for creating a Databricks Runtime ML cluster, see AI and machine learning on Databricks.
Note
Databricks Runtime ML releases pick up all maintenance updates to the base Databricks Runtime release. For a list of all maintenance updates, see Maintenance updates for Databricks Runtime (archived).
Libraries
Databricks Runtime 4.1 ML is built on top of Databricks Runtime 4.1. For information on what’s new in Databricks Runtime 4.1, see the Databricks Runtime 4.1 (EoS) release notes. In addition to the new features in Databricks Runtime 4.1, Databricks Runtime 4.1 ML includes the following libraries to support machine learning. Some of these are also included in the base Databricks Runtime 4.1 and are noted as such.
Category |
Libraries |
---|---|
Distributed Deep Learning |
Distributed training with Horovod and Spark:
Distributed TensorFlow and Keras prediction:
|
Deep Learning |
[Keras]:
GPU libraries:
|
XGBoost |
|
Other machine learning libraries |
|