The Visual Studio Code (VS Code) extension for Azure Machine Learning is now generally available. It allows users to use their favorite VS Code environment – whether desktop or web – to build, train, deploy, and manage machine learning models. It also provides features such as VNET (virtual network) support and interactive debugging, which aim to improve productivity and collaboration.
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What is Azure Machine Learning?
Azure Machine Learning is Microsoft’s cloud-based service that supports building, training, deploying and managing machine learning models. Users can use well-known open source tools such as TensorFlow, PyTorch or Jupyter, perform experiments locally and then scale up to large GPU clusters in the cloud. The VS Code extension provides a user interface for managing Azure ML resources and supports the new Azure ML 2.0 CLI.
To use the VS Code extension, users can connect to their preferred compute instances through Azure Machine Learning Studio. After registration, machine learning models can be developed directly in VS Code.
Users can navigate to the Compute section in Azure Machine Learning Studio and select the desired instance (web or desktop).
(Picture: Microsoft DevBlogs,
More information about the extension The blog post offers, Tutorials and Documentation are also available to help you get started. The extension is over Visual Studio Marketplace,
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