Welcome to a hands-on exercise using the Azure Machine Learning service and AI insights in Power BI Dataflows.
The learning in this exercise is to learn how to create and deploy ML models using the Azure Machine Learning service and then to consume them using AI insights in Power BI Dataflows.
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Need an Azure Subscription for this demo. If you do not have an Azure account, you can sign up for free here
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Need to create a Machine Learning service workspace in an Azure Resource Group
You can find details on creating an AML service workspace here
- Save the csv file carprice.csv that is available here
You can also get the file by downloading a zip of this repository or by cloning this GitHub repository using Git and the following commands:
git clone https://github.com/Azure/carprice.git
To learn how to create and deploy a ML model for the carprice dataset using the Azure Machine Learning service Workspace2 AML Preview Automated machine learning UI click here
To learn how to create and deploy a ML model for the carprice dataset using the Azure Machine Learning service Azure Portal Automated machine learning UI click here
To learn how to create and deploy a ML model for the carprice dataset using the Azure Machine Learning service Notebook VM click here
To learn how to create and deploy a ML model for the carprice dataset using the Azure Machine Learning service Visual interface click here
To learn how to use the carprice ML model to predict the price of a car using AI insights in Power BI click here
At the time of creating this Repo decorating the web service so that it is usable in AI insights in a Power BI Dataflow was not available when using the AML service Visual interface. This will not be the case as we move into fall 2019 when this scenario will also work from the Visual interface.
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