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Tutorial: Deploy Azure Machine Learning as an IoT Edge module (preview)

Use Azure Notebooks to develop a machine learning module and deploy it to a Linux device running Azure IoT Edge.

This tutorial walks you through deploying an Azure Machine Learning module that predicts when a device fails based on simulated machine temperature data.

The Azure Machine Learning module that you create in this tutorial reads the environmental data generated by your device and labels the messages as anomalous or not.

By completing all the steps in the notebook, you trained an anomaly detection model, built it as a Docker container image, and pushed that image to Azure Container Registry.

Check that your container image was successfully created and stored in the Azure container registry associated with your machine learning environment.

The notebook that you used in the previous section automatically provided the container image and the registry credentials to your IoT Edge device, but you should know where they're stored so that you can find the information yourself later.

If you created the IoT hub inside an existing resource group that has resources that you want to keep, delete only the IoT hub resource itself, instead of deleting the resource group.