Azure Machine Learning Curated Environments

This article provides an overview of the curated environments in Azure Machine Learning, detailing their benefits and usage. Curated environments are provided by Azure Machine Learning and are available in your workspace by default. The curated environments rely on cached Docker images that use the latest version of the Azure Machine Learning SDK. Using a curated environment can reduce the run preparation cost and allow for faster deployment time. Use these environments to quickly get started with various machine learning frameworks.


Use the Python SDK, CLI, or Azure Machine Learning studio to get the full list of environments and their dependencies. For more information, see the environments article.

Why should I use curated environments?

  • Reduces training and deployment latency.
  • Improves training and deployment success rate.
  • Avoid unnecessary image builds.
  • Only have required dependencies and access right in the image/container.


For more information about curated environment packages and versions, see How to manage environments in the Azure Machine Learning studio.