Jump into Microsoft’s drag-and-drop machine learning studio with this hands-on tutorial Machine learning is fast becoming the go-to predictive paradigm for data scientists and developers alike.

Dr. McCaffrey walks you through how to use the Microsoft Azure Machine Learning Studio, a new front-end for Microsoft Azure Machine Learning, to get a neural prediction system up and running.

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

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.

The VS Code extension for Azure Machine Learning enables the creation, training and management of ML models directly in Microsoft's code editor.

The ‘Machine Learning lifecycle management and possibilities with Azure Machine Learning’ webinar presented exciting insights and an interesting demo.

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.

To spot faults quickly even if they take a month to show up, Azure feeds signals into a machine learning system: in the future, you will be able to do that for your own cloud workloads.

Microsoft is joining the Databricks-backed MLflow project for machine learning experiment management. Already present in Azure Databricks, a fully managed version of MLflow will be added to Azure ...