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Copy file name to clipboardExpand all lines: articles/machine-learning/how-to-add-users.md
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ms.service: machine-learning
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ms.subservice: mldata
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ms.topic: how-to
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ms.date: 02/08/2023
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ms.date: 03/12/2024
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# customer intent: As a data labeling project manager, I want to add users to my data labeling project so that they can label data, but with restricted permissions.
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---
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# Add users to your data labeling project
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## Add custom role
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To add a custom role, you must have `Microsoft.Authorization/roleAssignments/write` permissions for your subscription - for example, [User Access Administrator](../../articles/role-based-access-control/built-in-roles.md).
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When you add a user to your project, you assign them a role to define their level of access. Before you add users, define the roles you want to use.
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1. Open your workspace in [Azure Machine Learning studio](https://ml.azure.com)
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1. Open the menu on the top right, and select **View all properties in Azure Portal**. You use the Azure portal for the remaining steps in this article.
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1. Select the **Resource group** link in the middle of the page.
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1. On the left, select **Access control (IAM)**.
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1. At the top, select **+ Add > Add custom role**.
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1. For the **Custom role name**, type the name you want to use. For example, **Labeler**.
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1. In the **Description** box, add a description. For example, **Labeler access for data labeling projects**.
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1. Select **Start from JSON**.
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1. At the bottom of the page, select **Next**.
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1. Don't do anything for the **Permissions** tab. You add permissions in a later step. Select **Next**.
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1. The **Assignable scopes** tab shows your subscription information. Select **Next**.
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1. In the **JSON** tab, above the edit box, select **Edit**.
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1. Select lines starting with **"actions:"** and **"notActions:"**.
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There is a built-in role for data labeling, scoped only to labeling data. If you want to use the built-in role for all your labelers, skip this section and proceed to [add guest user](#add-guest-user).
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The following custom roles give other levels of access for a data labeling project. Define all the roles you want to use before moving on to add the users.
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To add a custom role, you must have `Microsoft.Authorization/roleAssignments/write` permissions for your subscription - for example, [User Access Administrator](../../articles/role-based-access-control/built-in-roles.md).
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:::image type="content" source="media/how-to-add-users/replace-lines.png" alt-text="Create custom role: select lines to replace them in the editor.":::
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1. Access the resource group for your workspace in the Azure portal.
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1. Open your workspace in [Azure Machine Learning studio](https://ml.azure.com).
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1. Open the menu on the top right, and select **View all properties in Azure Portal**. You use the Azure portal for the remaining steps in this section.
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1. Select the **Resource group** link in the middle of the page.
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1. Add a custom role
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1. On the left, select **Access control (IAM)**.
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1. At the top, select **+ Add > Add custom role**.
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1. For the **Custom role name**, type the name you want to use. For example, **Labeling team lead**.
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1. In the **Description** box, add a description. For example, **Team leader for labeling projects**.
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1. Select **Start from JSON**.
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1. Ignore the **Select a file** entry, even though it is starred. You'll create the JSON in a future step.
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1. At the bottom of the page, select **Next**.
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1. Skip tabs.
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1. Don't do anything for the **Permissions** tab. You add permissions in a later step. Select **Next**.
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1. The **Assignable scopes** tab shows your subscription information. Select **Next**.
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1. Edit the JSON definition.
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1. In the **JSON** tab, above the edit box, select **Edit**.
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1. Select lines starting with **"actions:"** and **"notActions:"**.
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1. Replace these two lines with the `Actions` and `NotActions` from the appropriate role listed at [Manage access to an Azure Machine Learning workspace](how-to-assign-roles.md#data-labeling). Make sure to copy from `Actions` through the closing bracket, `],`
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:::image type="content" source="media/how-to-add-users/replace-lines.png" alt-text="Create custom role: select lines to replace them in the editor.":::
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1. Select **Save** at the top of the edit box to save your changes.
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1. Replace these two lines with the `Actions` and `NotActions` from the appropriate role in the following tabs. Make sure to copy from `Actions` through the closing bracket, `],`.
1. Select **Save** at the top of the edit box to save your changes.
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> [!IMPORTANT]
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> Don't select **Next** until you've saved your edits.
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## Add guest user
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If your labelers are outside of your organization, add them, so they can access your workspace. If labelers are already inside your organization, skip this step.
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If your labelers are outside of your organization, add them, so they can access your workspace. If labelers are already inside your organization, skip this step and proceed to [add users to your workspace](#add-users-to-your-workspace).
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To add a guest user, your organization's external collaboration settings need the correct configuration to allow you to invite guests.
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:::image type="content" source="media/how-to-add-users/invite-user.png" alt-text="Invite guest user from Microsoft Entra ID.":::
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Repeat these steps for each of your labelers. You can also use the link at the bottom of the **Invite user** box to invite multiple users in bulk.
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Repeat these steps for each of the guest users. Or use the link at the bottom of the **Invite user** box to invite multiple users in bulk.
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> [!TIP]
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> Inform your labelers that they will receive this email. They must accept the invitation in order to gain access to your project.
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> Inform your labelers that they will receive an email. They must accept the invitation in order to gain access to your project.
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## Add users to your workspace
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Now that you added your labelers to the system, you can add them to your workspace.
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Once you have the appropriate users in your system and the role(s) defined, add the users to your workspace so that they can access your data labeling project.
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To add users to your workspace, you must be an owner of the workspace.
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1. In [Azure portal](https://portal.azure.com), in the top search field, type **Machine Learning**.
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1. Select **Machine Learning**.
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:::image type="content" source="media/how-to-manage-workspace/find-workspaces.png" alt-text="Search for Azure Machine Learning workspace.":::
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1. Select the workspace that contains your data labeling project.
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1. Access your workspace in the Azure portal.
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1. Open your workspace in [Azure Machine Learning studio](https://ml.azure.com).
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1. Open the menu on the top right, and select **View all properties in Azure Portal**. You use the Azure portal for the remaining steps in this section.
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1. On the left, select **Access control (IAM)**.
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1. At the top, select **+ Add > Add role assignment**.
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:::image type="content" source="media/how-to-add-users/add-role-assignment.png" alt-text="Add role assignment from your workspace.":::
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1. Select the **Labeler** or **Labeling Team Lead** role in the list. Use **Search** if necessary to find it.
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1. Select the role you want to use from the list. Use **Search** if necessary to find it.
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1. Select **Next**.
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1. In the middle of the page, next to **Members**, select the **+ Select members** link.
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1. Select each of the users you want to add. Use **Search** if necessary to find them.
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## For your labelers
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Now, your labelers can begin labeling in your project. However, they still need information from you to access the project.
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Once labelers have been added as users in the workspace, they can begin labeling in your project. However, they still need information from you to access the project.
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Be sure to create your labeling project before you contact your labelers.
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1. Open [Azure Machine Learning studio](https://ml.azure.com).
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1. Use the dropdown to select the workspace **\<workspace-name\>**.
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1. Select the **Label data** tool for **\<project-name\>**.
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:::image type="content" source="media/how-to-add-users/label-data.png" alt-text="Screenshot showing the label data tool.":::
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:::image type="content" source="media/how-to-add-users/label-data.png" alt-text="Screenshot shows the label data tool in a project.":::
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1. For more information about how to label data, see [Labeling images and text documents](how-to-label-data.md).
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## Next steps
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## Related content
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* Learn more about [working with a data labeling vendor company](how-to-outsource-data-labeling.md)
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*[Create an image labeling project and export labels](how-to-create-image-labeling-projects.md)
Copy file name to clipboardExpand all lines: articles/machine-learning/how-to-assign-roles.md
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### Data labeling
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# [Data labeler](#tab/labeler)
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There is a built-in role for data labeling, scoped only to labeling data. The following custom roles give other levels of access for a data labeling project.
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Allows you to define a role scoped only to labeling data:
Allows you to review and reject the labeled dataset and view labeling insights. In addition to it, this role also allows you to perform the role of a labeler.
A vendor account manager can help manage all the vendor roles and perform any labeling action. They can't modify projects or view MLAssist experiments.
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*vendor_admin_role.json* :
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```json
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{
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"Name": "Vendor account admin",
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"IsCustom": true,
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"Description": "Vendor account admin for Labeling Projects",
A customer quality assurance role can view project dashboards, preview datasets, export a labeling project, and review submitted labels. This role can't submit labels.
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*customer_qa_role.json* :
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```json
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{
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"Name": "Customer QA",
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"IsCustom": true,
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"Description": "Customer QA for Labeling Projects",
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