What is Azure Machine Learning studio?

• 08/24/2020
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In this article, you learn about Azure Machine Learning studio, the web portal for data scientist developers in Azure Machine Learning. The studio combines no-code and code-first experiences for an inclusive data science platform.

In this article you learn:

We recommend that you use the most up-to-date browser that's compatible with your operating system. The following browsers are supported:

• Microsoft Edge (The new Microsoft Edge, latest version. Not Microsoft Edge legacy)
• Safari (latest version, Mac only)
• Chrome (latest version)
• Firefox (latest version)

Author machine learning projects

The studio offers multiple authoring experiences depending on the type project and the level of user experience.

• Notebooks

  Write and run your own code in managed Jupyter Notebook servers that are directly integrated in the studio.

• Azure Machine Learning designer

  Use the designer to train and deploy machine learning models without writing any code. Drag and drop datasets and modules to create ML pipelines. Try out the designer tutorial.

  

• Automated machine learning UI

  Learn how to create automated ML experiments with an easy-to-use interface.

  

• Data labeling

  Use Azure Machine Learning data labeling to efficiently coordinate data labeling projects.

Manage assets and resources

Manage your machine learning assets directly in your browser. Assets are shared in the same workspace between the SDK and the studio for a seamless experience. Use the studio to manage:

• Models
• Datasets
• Datastores
• Compute resources
• Notebooks
• Experiments
• Run logs
• Pipelines
• Pipeline endpoints

Even if you're an experienced developer, the studio can simplify how you manage workspace resources.

ML Studio (classic) vs Azure Machine Learning studio

Released in 2015, ML Studio (classic) was our first drag-and-drop machine learning builder. It is a standalone service that only offers a visual experience. Studio (classic) does not interoperate with Azure Machine Learning.

Azure Machine Learning is a separate and modernized service that delivers a complete data science platform. It supports both code-first and low-code experiences.

Azure Machine Learning studio is a web portal in Azure Machine Learning that contains low-code and no-code options for project authoring and asset management.

We recommend that new users choose Azure Machine Learning, instead of ML Studio (classic), for the latest range of data science tools.

Feature comparison

The following table summarizes the key differences between ML Studio (classic) and Azure Machine Learning.

Troubleshooting

• Missing user interface items in studio Azure role-based access control can be used to restrict actions that you can perform with Azure Machine Learning. These restrictions can prevent user interface items from appearing in the Azure Machine Learning studio. For example, if you are assigned a role that cannot create a compute instance, the option to create a compute instance will not appear in the studio. For more information, see Manage users and roles.

Next steps

Visit the studio, or explore the different authoring options with these tutorials:

• • Get started in your own development environment
  • Use Jupyter notebooks on a compute instance to train & deploy models
  • Use automated machine learning to train & deploy models
  • Use the designer to train & deploy models
  • Use studio in a secured virtual network