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.

Prerequisites

1. Need an Azure Subscription for this demo. If you do not have an Azure account, you can sign up for free here

2. Need to create a Machine Learning service workspace in an Azure Resource Group

You can find details on creating an AML service workspace here

3. 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

Using the NEW Workspace2 AML Preview Automated machine learning UI

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

Using the Azure Portal Automated machine learning UI

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

Using the Notebook VM

To learn how to create and deploy a ML model for the carprice dataset using the Azure Machine Learning service Notebook VM click here

Using the Visual interface

To learn how to create and deploy a ML model for the carprice dataset using the Azure Machine Learning service Visual interface click here

Using AI insights in Power BI

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.

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Legal Notices

Microsoft and any contributors grant you a license to the Microsoft documentation and other content in this repository under the Creative Commons Attribution 4.0 International Public License, see the LICENSE file, and grant you a license to any code in the repository under the MIT License, see the LICENSE-CODE file.

Microsoft, Windows, Microsoft Azure and/or other Microsoft products and services referenced in the documentation may be either trademarks or registered trademarks of Microsoft in the United States and/or other countries. The licenses for this project do not grant you rights to use any Microsoft names, logos, or trademarks. Microsoft's general trademark guidelines can be found at http://go.microsoft.com/fwlink/?LinkID=254653.

Privacy information can be found at https://privacy.microsoft.com/en-us/

Microsoft and any contributors reserve all other rights, whether under their respective copyrights, patents, or trademarks, whether by implication, estoppel or otherwise.

Add to test connection to GitHub