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‎.openpublishing.redirection.json‎

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"source_path": "docs/azure-data-studio/schema-compare-extension.md",
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"redirect_url": "/sql/azure-data-studio/extensions/schema-compare-extension",
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"redirect_document_id": true
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},
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{
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"source_path": "docs/azure-data-studio/sql-database-project-extension-build-from-command-line.md",
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"redirect_url": "/sql/azure-data-studio/extensions/sql-database-project-extension-build-from-command-line",
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"redirect_document_id": true
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{
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"source_path": "docs/azure-data-studio/sql-database-project-extension-build.md",
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"redirect_document_id": true
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"source_path": "docs/azure-data-studio/sql-database-project-extension-getting-started.md",
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"source_path": "docs/azure-data-studio/sql-database-project-extension.md",
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"redirect_url": "/sql/azure-data-studio/extensions/sql-database-project-extension",
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"redirect_document_id": true
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"redirect_document_id": true
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"redirect_document_id": true
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"source_path": "docs/azure-data-studio/sql-server-dacpac-extension.md",
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"redirect_url": "/sql/azure-data-studio/extensions/sql-server-dacpac-extension",
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"redirect_document_id": true
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"source_path": "docs/azure-data-studio/sql-server-import-extension.md",
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"redirect_document_id": true
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‎docs/azure-data-studio/extensions/add-extensions.md‎

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author: "markingmyname"
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ms.author: "maghan"
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ms.reviewer: "alayu, maghan, sstein"
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ms.custom: "seodec18"
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ms.date: "10/03/2019"
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‎docs/azure-data-studio/extensions/azure-arc-extension.md‎

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---
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title: Azure Arc extension (preview)
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description: Learn how to install and use the Azure Arc extension to try out Azure Arc data services.
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ms.reviewer: "alayu, maghan, sstein"
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ms.prod: azure-data-studio
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ms.technology: azure-data-studio
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ms.topic: conceptual
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author: "yualan"
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ms.author: "alayu"
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ms.custom: "seodec18"
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ms.date: "09/22/2020"
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author: yualan
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ms.author: alayu
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ms.reviewer: maghan, sstein
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ms.custom:
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ms.date: 09/22/2020
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# Azure Arc extension for Azure Data Studio (Preview)

‎docs/azure-data-studio/extensions/azure-sql-managed-instance-extension.md‎

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‎docs/azure-data-studio/extensions/dashboard-extension.md‎

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description: This tutorial demonstrates how to create a dashboard extension to add custom functionality to Azure Data Studio.
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ms.prod: azure-data-studio
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ms.technology: azure-data-studio
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ms.reviewer: alayu, maghan
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‎docs/azure-data-studio/extensions/data-virtualization-extension.md‎

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‎docs/azure-data-studio/extensions/extension-authoring.md‎

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‎docs/azure-data-studio/extensions/keymap-extension.md‎

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description: This tutorial demonstrates how to create a keymap extension to add custom functionality to Azure Data Studio.
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ms.reviewer: alayu, maghan
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‎docs/azure-data-studio/extensions/kusto-extension.md‎

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docs/azure-data-studio/machine-learning-extension-import-view-models.md renamed to docs/azure-data-studio/extensions/machine-learning-extension-import-view-models.md

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Follow the steps below to view ONNX models that are stored in your database.
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1. Click on **Import or view models**.
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1. Select **Import or view models**.
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1. If you're asked to install **onnxruntime**, **mlflow**, and **mlflow-dbstore**, click **Yes**.
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1. If you're asked to install **onnxruntime**, **mlflow**, and **mlflow-dbstore**, select **Yes**.
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1. Select the **Models database** and **Models table** where your models are stored in.
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Follow the steps below to import an ONNX model in your database.
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1. Select **Import or view models**.
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1. If you're asked to install **onnxruntime**, **mlflow**, and **mlflow-dbstore**, click **Yes**.
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1. If you're asked to install **onnxruntime**, **mlflow**, and **mlflow-dbstore**, select **Yes**.
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1. Click **Import models**.
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1. Select **Import models**.
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1. Select the **Models table** you want to store the imported model in. You can either choose an **Existing table** or create a **New table**. Click **Next**.
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1. Select the **Models table** you want to store the imported model in. You can either choose an **Existing table** or create a **New table**. Select **Next**.
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1. Select where your model is located and click **Next**. You can use:
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- **File upload**. Choose this to use a model from a file. Select the model file under **Source files** and click **Next**.
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- **Azure Machine Learning**. Choose this to use a model from Azure Machine Learning. First, **Sign in to Azure**. Then select your **Azure account**, **Azure subscription**, **Azure resource group**, and **Azure ML workspace**. Select the model you want to use and click **Next**.
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1. Select where your model is located and Select **Next**. You can use:
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- **File upload**. Choose this to use a model from a file. Select the model file under **Source files** and Select **Next**.
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- **Azure Machine Learning**. Choose this to use a model from Azure Machine Learning. First, **Sign in to Azure**. Then select your **Azure account**, **Azure subscription**, **Azure resource group**, and **Azure ML workspace**. Select the model you want to use and Select **Next**.
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1. Enter the model **Name** and **Description** and click **Deploy** to store the model in your database.
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1. Enter the model **Name** and **Description** and Select **Deploy** to store the model in your database.
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> [!NOTE]
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> The Machine Learning extension is currently in preview. Therefore, the table schema where the models are stored might change in the future.
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- [Machine Learning extension in Azure Data Studio](machine-learning-extension.md)
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- [Manage packages in database](machine-learning-extension-manage-packages.md)
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- [Make predictions](machine-learning-extension-predictions.md)
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- [SQL machine learning documentation](../machine-learning/index.yml)
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- [SQL machine learning documentation](../../machine-learning/index.yml)
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- [Machine Learning Services in Azure SQL Managed Instance](/azure/azure-sql/managed-instance/machine-learning-services-overview)
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- [Machine learning and AI with ONNX in SQL Edge (Preview)](/azure/azure-sql-edge/onnx-overview)

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