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.

As you see above, the documentation for Azure Machine Learning Jupyter Notebooks comes in the form of a Jupyter Notebook. Cortana Analytics Process Earlier I mentioned the Cortana Analytics Process .

Matt Winkler delivered a talk at Microsoft Build 2018 explaining what is new in Azure Machine Learning. The new improvements come in several areas: making development easier, single container deployme ...

Microsoft dev teams for Azure Machine Learning (Azure ML) and Visual Studio Code have improved the developer experience in the super-popular, open source-based, cross-platform code editor. An update ...

Azure Machine Learning is a cloud-based service that allows data scientists or developers to train, build and deploy ML models. It has a rich set of tools that makes it easy to create predictive ...

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 ...

“When Azure Machine Learning arrives, it’s so easy to use, and the cost of producing an API is so low, it becomes easy for data scientists and developers to make fully machine learning APIs in ...

Azure ML comes with a full menu of out-of-the-box features for machine learning and even offers development templates to get started. Despite limiting customization, its pre-built offerings make ...