Azure Machine Learning supports five environments for model development: Azure Notebooks, the Data Science Virtual Machine (DSVM), Jupyter Notebooks, Visual Studio Code, and Azure Databricks.

If you’re familiar with Microsoft’s Cognitive Services tools, you can also use the Azure Machine Learning studio or a local development environment using Visual Studio Code.

Microsoft announced the Azure Machine Learning studio web experience is generally available with a bunch of new features. Here's what's new.

The Azure Machine Learning studio web experience is generally availabl, enabling data scientists and data engineers to complete their end-to-end machine learning lifecycle from prepping and ...

Azure Arc is Microsoft’s hybrid and multi-cloud platform that seamlessly extends the capabilities of Azure public cloud to on-prem data centers, edge locations, and any public cloud.

This capability allows customers to build models with Azure Machine Learning anywhere, including on-premises, multi-cloud environments, and at the edge.

The Visual Studio Code (VS Code) extension for Azure Machine Learning is now generally available. It enables users to use their favorite VS Code environment – whether desktop or web – to ...

This tool, the Azure Machine Learning visual interface, looks suspiciously like the existing Azure ML Studio, Microsoft’s first stab at building a visual machine learning tool.

The platform includes Azure Machine Learning Studio, a GUI-based integrated development environment for constructing and operationalizing machine learning workflows on the Azure cloud.

The Azure Machine Learning Studio was introduced way back in 2014. The new web offering helps developers build and train custom models, and then deploy and manage them to the cloud or edge, while ...