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Update custom-azure-machine-learning-algorithms.md #4969

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5 changes: 3 additions & 2 deletions articles/supply-chain/demand-planning/custom-azure-machine-learning-algorithms.md
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Expand Up @@ -20,8 +20,9 @@ ms.collection:

If you're already using your own Microsoft Azure Machine Learning algorithms for demand forecasting in Dynamics 365 Supply Chain Management (as described in [Demand forecasting overview](../master-planning/introduction-demand-forecasting.md)), you can continue to use them while you use the Demand planning app.

This article describes the setup that is required to enable the Demand planning app to connect to your [Azure Machine Learning workspace](/azure/machine-learning/concept-workspace).
If you don't have existing algorithms but you want to develop your own forecasting models, you can utilize [Custom-ML-in-DemandPlanning repository](https://github.com/microsoft/Dynamics-365-Demand-Planning-Custom-Azure-ML-Template). It provides a comprehensive demonstration of key aspects involved in integrating the Dynamics 365 Demand Planning application with Azure Machine Learning (Azure ML).

This article describes the setup that is required to enable the Demand planning app to connect to your [Azure Machine Learning workspace](/azure/machine-learning/concept-workspace).
## Set up a new Microsoft Entra application

Follow the steps in this section to create a new Microsoft Entra application in your Azure Machine Learning workspace. This resource in the [Azure portal](/azure/azure-portal/azure-portal-overview) holds your algorithms. The Microsoft Entra application is an enterprise application that enables the Demand planning app to connect to your Azure Machine Learning algorithms. (For more information about how to set up a Microsoft Entra application, see [Register an application](/entra/identity-platform/quickstart-register-app#register-an-application).)
Expand Down Expand Up @@ -83,5 +84,5 @@ Follow these steps to set up a forecast that uses your own Azure Machine Learnin
1. Create a new forecast profile as described in [Create and manage forecast profiles](forecast-profiles.md#create-profile).
1. On the **Select a forecasting model preset** page, select *None*.
1. After you've created and saved the profile, select the **Forecast model** tab. (For more information, see [Design forecast models](design-forecast-models.md).)
1. Set up your model. Include a **Finance and operations – Azure Machine Learning** tile in the position where you want to run your algorithm.
1. Set up your model. Include a **Finance and operations – Azure Machine Learning** tile in the position where you want to run your algorithm. If you developed your model based on [Custom-ML-in-DemandPlanning repository](https://github.com/microsoft/Dynamics-365-Demand-Planning-Custom-Azure-ML-Template) you need to use **Custom – Azure Machine Learning** tile instead.
1. Complete the model by adding a **Save** block.