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articles/active-directory/devices/faq.yml

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- For iOS and Android, you can use the Microsoft Authenticator application **Settings** > **Device Registration** and select **Unregister device**.
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- For macOS, you can use the Microsoft Intune Company Portal application to unenroll the device from management and remove any registration.
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For Windows 10/11 devices, this process can be automated with the [Workplace Join (WPJ) removal tool](https://download.microsoft.com/download/8/e/f/8ef13ae0-6aa8-48a2-8697-5b1711134730/WPJCleanUp.zip)
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For Windows 10 version 2004 and older, this process can be automated with the [Workplace Join (WPJ) removal tool](https://download.microsoft.com/download/8/e/f/8ef13ae0-6aa8-48a2-8697-5b1711134730/WPJCleanUp.zip)
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> [!NOTE]
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> This tool removes all SSO accounts on the device. After this operation, all applications will lose SSO state, and the device will be unenrolled from management tools (MDM) and unregistered from the cloud. The next time an application tries to sign in, users will be asked to add the account again.

articles/azure-functions/functions-proxies.md

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By default, the client response is initialized as a copy of the back-end response. You can make changes to the response's status code, reason phrase, headers, and body. The modified values can reference [application settings], [parameters from the original client request], and [parameters from the back-end response].
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Back-end requests can be modified in the portal by expanding the *response override* section of the proxy detail page.
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Back-end responses can be modified in the portal by expanding the *response override* section of the proxy detail page.
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## <a name="using-variables"></a>Use variables
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articles/machine-learning/how-to-use-batch-endpoint-sdk-v2.md

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* The [Azure Machine Learning SDK v2 for Python](/python/api/overview/azure/ml/installv2).
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## 1. Connect to Azure Machine Learning workspace
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## Connect to Azure Machine Learning workspace
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The [workspace](concept-workspace.md) is the top-level resource for Azure Machine Learning, providing a centralized place to work with all the artifacts you create when you use Azure Machine Learning. In this section, we'll connect to the workspace in which the job will be run.
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