Announcing the General Availability of the VS Code extension for Azure Machine Learning

Machine learning and artificial intelligence are changing the world as we know it. With the power of data, you will have countless opportunities to create new, unique, and interesting things. Whether you are a seasoned data scientist or a curious beginner, you need a platform that allows you to build, train, deploy, and manage your machine learning models easily and efficiently. Azure Machine Learning has always been a mainstay of machine learning work, and we want to further help you on your machine learning journey by improving the way you write code.

that VS Code Extensions for Azure Machine Learning It’s been in preview for a while now and we’re excited to announce it. VS Code Extensions For Azure Machine Learning. Build, train, deploy, debug, and manage machine learning models with Azure Machine Learning from within VS Code, using your favorite VS Code settings on the desktop or web. That means this extension is stable, reliable, and production-ready, with additional features like VNET support. Updates roll out throughout the day.

Azure Machine Learning Extension for VS Code

“We’ve been using the VS Code extension for Azure Machine Learning since its preview release, and it has streamlined our workflow significantly. The ability to manage everything from building models to deploying them in our preferred VS Code environment has been a game changer. The seamless integration and powerful features like interactive debugging and VNET support have enhanced our productivity and collaboration. We’re excited for the general availability of this extension and look forward to leveraging its full potential on our AI projects.” –Ornaldo Rivas Pernandes: Co-founder and CEO, Passable

Azure Machine Learning

Azure Machine Learning (Azure ML) is a cloud-based service that lets you build, train, deploy, and manage machine learning models.

Azure Machine Learning service allows you to:

• Build and train machine learning models faster, and easily deploy them to the cloud or edge.
• Use the latest open source technologies like TensorFlow, PyTorch, and Jupyter.
• Experiment locally, then quickly scale up or scale out using large GPU-enabled clusters in the cloud.
• Debug your experiments, pipelines, and deployments interactively using the built-in VS Code debugger.
• Accelerate data science with automated machine learning and hyperparameter tuning.
• Track experiments, manage models, and deploy easily using integrated CI/CD tools.

With this extension, you can perform most of this workflow directly in Visual Studio Code. The VS Code extension provides a user interface for creating and managing Azure ML resources, such as experiments, compute targets, environments, and deployments. It also supports the Azure ML 2.0 CLI, a new command-line tool that simplifies the specification and execution of machine learning jobs.

Getting started with the Azure Machine Learning extension

Connect to VS Code from Azure ML Studio with one click

To get started with VS Code, go to the Compute section. Azure Machine Learning Studio. Find the compute instance you want and click the VS Code (Web) or VS Code (Desktop) link under the “Applications” section.

Don’t have an Azure ML workspace or compute instance? Check out our guide here. Tutorial: Create a Workspace Resource – Azure Machine Learning | Microsoft Learn

How to connect in Azure ML Studio

VS Code Desktop

When you click the VS Code Desktop link, your browser will ask for permission to launch the VS Code desktop application. VS Code Desktop will ask you to sign in using your Microsoft/Azure account.

Follow the login prompts and you’re all set to develop your own machine learning models using your favorite VS Code settings!

VS Code Web

When you click the link, VS Code (Web) will open in a new tab in your browser. You may be prompted to sign in using your Microsoft/Azure account, so VS Code has access to your Azure subscription and workspace. The connection process may take a few minutes.

After you log in, you should now be connected to your Azure Machine Learning workspace inside VS Code. It’s time to use all the power of VS Code to build your own machine learning models!

Connect to VS Code Web

feedback

Try out the Azure Machine Learning extension and let us know what you think. If you have any questions or feedback, please share your thoughts in this post. inspection! You can also raise issues on public sites. GitHub repo Please feel free to contact us with any questions or concerns.

Need a guide or documentation to help you get started? Check out our tutorials here: Azure Machine Learning documentation | Microsoft Learn