To choose your default workspace, select the Set Azure ML Workspace button on the Visual Studio Code status bar and follow the prompts to set your workspace.Īlternatively, use the > Azure ML: Set Default Workspace command in the command palette and follow the prompts to set your workspace. For more information, see manage Azure Machine Learning resources with the VS Code extension. If you don't have a workspace, create one. Choose your default workspaceĬhoosing a default Azure Machine Learning workspace enables the following when authoring CLI (v2) YAML specification files: VS Code provides several different scopes for settings. Nearly every part of VS Code's editor, user interface, and functional behavior has options you can modify. To sign into you Azure account, select the Azure: Sign In button in the bottom right corner on the Visual Studio Code status bar to start the sign in process. You can configure Visual Studio Code to your liking through its various settings. Visit the following site to learn more about the Azure Account extension. To assist with account management, Azure Machine Learning automatically installs the Azure Account extension. In order to provision resources and run workloads on Azure, you have to sign in with your Azure account credentials. For more information on modifying your settings in Visual Studio, see the user and workspace settings documentation. To switch to the 1.0 CLI, set the azureML.CLI Compatibility Mode setting in Visual Studio Code to 1.0. The Azure Machine Learning VS Code extension uses the CLI (v2) by default. In most cases, you will have a single folder opened as the workspace but, depending on your development workflow, you can include more than one folder, using an advanced configuration called Multi-root workspaces. In the Extensions view search bar, type "Azure Machine Learning" and select the first extension. A Visual Studio Code 'workspace' is the collection of one or more folders that are opened in a VS Code window (instance). Select Extensions icon from the Activity Bar to open the Extensions view. For setup instructions, see Install, set up, and use the CLI (v2).
#Visual studio code workspace install#
If you don't have one, sign up to try the free or paid version of Azure Machine Learning. Schema-based language support, autocompletion and diagnostics for specification file authoring.Debug machine learning experiments locally.Develop locally using remote compute instances.
#Visual studio code workspace how to#
Learn how to set up the Azure Machine Learning Visual Studio Code extension for your machine learning workflows.