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Azure ML Studio

service · part of Azure ML Service

A web-based interface for managing Azure Machine Learning resources, including notebooks and compute instances.

The workspace is accessed via the Azure Machine Learning studio at ml.azure.com. It contains assets such as Data, Datastores, and connections.

Data assets (formerly datasets) are immutable references to data created from datastores, local files, public URLs, or open datasets. They are located under Assets -> Data in the studio. In AzureML v2 APIs, data assets cannot be deleted, only up-versioned or archived; in v1 APIs, they are permanently deleted when removed.

Default datastores include workspaceworkingdirectory (stores working directory, Jupyter notebooks) and workspaceblobstore (used for ML job data).

Inside Azure ML Studio (7)

• Azure ML Python Kernel — The default Python kernel in Azure ML Studio that includes necessary ML libraries for course notebooks.
• Compute Instance — A cloud-based virtual machine for running notebook code cells, provisioned within Azure ML Studio.
• Focus Mode — A workspace mode in Azure ML Studio that expands the notebook editing area by hiding side panels.
• IntelliSense — A code completion feature available in Azure ML Studio notebooks.
• Jupyter Notebook — An interactive document format (.ipynb) for code, text, and visualizations, supported in Azure ML Studio.
• JupyterLab — An alternative notebook editing environment accessible from the compute instance in Azure ML Studio.
• VS Code for Web — A browser-based code editor launched from Azure ML Studio that runs against a compute instance.

Also known as: Azure ML Studio, ML Studio

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