Machine learning is fast becoming the go-to predictive paradigm for data scientists and developers alike. Of the many tools available for tapping neural networks, Microsoft’s Azure ML Studio ...

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.

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 ...

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.

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

The new interface for Azure’s automated machine learning tool makes creating a model as easy as importing a data set and then telling the service which value to predict. Users don’t need to ...

The original Azure Machine Learning service -- now called Azure Machine Learning Studio -- was a sort of visual development environment for doing machine learning (ML) work.

Already present in Azure Databricks, a fully managed version of MLflow will be added to Azure Machine Learning and made available soon. Written by Andrew Brust, Contributor April 24, 2019, 9:00 a ...