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FAQ
With the Azure Machine Learning for Visual Studio Code extension you can easily build, train, and deploy machine learning models to the cloud or the edge with Azure Machine Learning service from the Visual Studio Code interface. Earlier versions of this extension were released under the name Visual Studio Code Tools for AI.
The Azure Machine Learning extension for VS Code provides a user interface to:
- Manage Azure Machine Learning resources (experiments, virtual machines, models, deployments, etc.)
- Develop locally using remote compute instances
- Train machine learning models
- Debug machine learning experiments locally
- Schema-based language support, autocompletion and diagnostics for specification file authoring
This extension is complementary to the Azure Machine Learning extension and is used to seamlessly connect VS Code to a remote Compute Instance.
Once connected to the compute instance, you can:
- Run and debug Python scripts and Notebooks, executing directly on the CI
- Traverse the remote filesystem and mounted fileshare
- Invoke commands in a remote terminal
- Clone and manage git repos
To set up Azure Machine Learning extension in VSCode, follow the instructions here
To connect to a remote Compute instance using Azure ML extension, follow the instructions here
How to interactively debug Azure Machine Learning experiments, pipelines, and deployments using Azure ML extensions in VSCode ?
To use interactive debugging in VSCode using Azure ML extension, follow the instructions here
To learn how to manage Azure Machine Learning resources with the VS Code extension, follow the instructions here
How to train an image classification model using TensorFlow and the Azure Machine Learning Extension ?
To learn how to train an image classification model to recognize hand-written numbers using TensorFlow and the Azure Machine Learning Visual Studio Code Extension, follow the instructions here
In case the latest version of the extension is not working for you, please open an issue in our repo. In the meanwhile, you can install a previous version of the extension by following the steps here