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‎articles/machine-learning/data-science-virtual-machine/dsvm-tools-data-platforms.md

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| ------------- | ------------- |
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| What is it? | A local relational database instance |
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| Supported DSVM editions | Windows: SQL Server 2017, Windows 2019 (Preview) : SQL Server 2019 |
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| Supported DSVM editions | Windows 2016: SQL Server 2017, Windows 2019: SQL Server 2019 |
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| Typical uses | Rapid development locally with smaller dataset <br/> Run In-database R |
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| Links to samples | A small sample of a New York City dataset is loaded into the SQL database:<br/> `nyctaxi` <br/> Jupyter sample showing Microsoft Machine Learning Server and in-database analytics can be found at:<br/> `~notebooks/SQL_R_Services_End_to_End_Tutorial.ipynb` |
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| Related tools on the DSVM | SQL Server Management Studio <br/> ODBC/JDBC drivers<br/> pyodbc, RODBC<br />Apache Drill |

‎articles/machine-learning/data-science-virtual-machine/dsvm-tools-data-science.md

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| What is it? | Open-source SQL query engine on big data |
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| Supported DSVM versions | Windows 2019 (Preview), Linux |
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| Supported DSVM versions | Windows 2019, Linux |
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| How is it configured and installed on the DSVM? | Installed in `/dsvm/tools/drill*` in embedded mode only |
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| Typical uses | For in-place data exploration without requiring extract, transform, load (ETL). Query different data sources and formats, including CSV, JSON, relational tables, and Hadoop. |
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| How to use and run it | Desktop shortcut <br/> [Get started with Drill in 10 minutes](https://drill.apache.org/docs/drill-in-10-minutes/) |

‎articles/machine-learning/data-science-virtual-machine/dsvm-tools-development.md

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| What is it? | General purpose IDE |
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| Supported DSVM versions | Windows: Visual Studio 2017, Windows 2019 (Preview) : Visual Studio 2019 |
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| Supported DSVM versions | Windows: Visual Studio 2017, Windows 2019 : Visual Studio 2019 |
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| Typical uses | Software development |
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| How is it configured and installed on the DSVM? | Data Science Workload (Python and R tools), Azure workload (Hadoop, Data Lake), Node.js, SQL Server tools, [Azure Machine Learning for Visual Studio Code](https://github.com/Microsoft/vs-tools-for-ai) |
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| How to use and run it | Desktop shortcut (`C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\Common7\IDE\devenv.exe`). Graphically, open Visual Studio by using the desktop icon or the **Start** menu. Search for programs (Windows logo key+S), followed by **Visual Studio**. From there, you can create projects in languages like C#, Python, R, and Node.js. |
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| What is it? | Client IDE for Python language |
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| Supported DSVM versions | Windows 2019 (Preview), Linux |
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| Supported DSVM versions | Windows 2019, Linux |
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| Typical uses | Python development |
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| How to use and run it | Desktop shortcut (`C:\Program Files\tk`) on Windows. Desktop shortcut (`/usr/bin/pycharm`) on Linux |
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| Related tools on the DSVM | Visual Studio, Visual Studio Code, RStudio |

‎articles/machine-learning/data-science-virtual-machine/dsvm-tools-productivity.md

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In addition to the data science and programming tools, the DSVM contains productivity tools to help you capture and share insights with your colleagues. Office 365 ProPlus is the most productive and most secure Office experience for enterprises, allowing your teams to work together seamlessly from anywhere, anytime. With Power BI Desktop you can go from data to insight to action. And the Microsoft Edge browser is a modern, fast, and secure Web browser.
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| Tool | Windows DSVM | Linux DSVM | Windows 2019 Server DSVM (Preview) | Ubuntu 19.04 DSVM (Preview) | Usage notes |
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| Tool | Windows DSVM | Linux DSVM | Windows 2019 Server DSVM | Ubuntu 18.04 DSVM | Usage notes |
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|----------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------------------------|
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| [Microsoft Office](https://www.microsoft.com/p/office-365-proplus/CFQ7TTC0K8R0) ProPlus with shared activation: Excel, Word, and PowerPoint | <span class='green-check'>&#9989;</span> | <span class='red-x'>&#10060;</span> | <span class='green-check'>&#9989;</span> | <span class='red-x'>&#10060;</span> | You may activate Office either using:<br/><ul><li> Your own Microsoft account<li>Key Management Service (see [Activate volume licensed versions of Office by using KMS](https://docs.microsoft.com/deployoffice/vlactivation/activate-office-by-using-kms)) <li> Multiple Activation Key (see [Activate volume licensed versions of Office by using MAK](https://docs.microsoft.com/deployoffice/vlactivation/activate-office-by-using-mak))</ul> |
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| [Power BI Desktop](https://powerbi.microsoft.com/) | <span class='green-check'>&#9989;</span></br> (2.73.55xx) | <span class='red-x'>&#10060;</span> | <span class='green-check'>&#9989;</span></br> (2.73.55xx) | <span class='red-x'>&#10060;</span> | |

‎articles/machine-learning/data-science-virtual-machine/geo-ai-dsvm-overview.md

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# What is the Geo Artificial Intelligence Data Science Virtual Machine?
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The Geo Artificial Intelligence Data Science Virtual Machine (also known as Geo AI Data Science VM, or Geo-DSVM) delivers geospatial analytics capabilities from the Azure Data Science Virtual Machine (DSVM). Specifically, this VM extends the AI and data science toolkits in the [DSVM](overview.md) by adding the market-leading [ArcGIS Pro](https://www.esri.com/arcgis/products/arcgis-pro/overview) geographic information system from ERSI.
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The Geo Artificial Intelligence Data Science Virtual Machine (also known as Geo AI Data Science VM, or Geo-DSVM) delivers geospatial analytics capabilities from the Azure Data Science Virtual Machine (DSVM). Specifically, this VM extends the AI and data science toolkits in the [DSVM](overview.md) by adding the market-leading [ArcGIS Pro](https://www.esri.com/arcgis/products/arcgis-pro/overview) geographic information system from ESRI.
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Geo AI Data Science VM is a product offering that arose out of the collaboration between ESRI and Microsoft. The result is a powerful environment that provides the ability to:
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‎articles/machine-learning/data-science-virtual-machine/overview.md

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The Data Science Virtual Machine (DSVM) is a customized VM image on the Azure cloud platform built specifically for doing data science. It has many popular data science tools preinstalled and preconfigured to jumpstart building intelligent applications for advanced analytics.
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The DSVM is available on:
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+ **Windows Server 2019 (Preview)**
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+ **Ubuntu 18.04 LTS (Preview)**
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+ **Windows Server 2019**
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+ **Ubuntu 18.04 LTS**
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+ Windows Server 2016
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+ Ubuntu 16.04 LTS and CentOS 7.4
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‎articles/machine-learning/data-science-virtual-machine/provision-vm.md

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To create a DSVM instance:
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1. Go to the [Azure portal](https://portal.azure.com) You might be prompted to sign in to your Azure account if you're not already signed in.
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1. Find the virtual machine listing by typing in "data science virtual machine" and selecting "Data Science Virtual Machine - Win 2019 (Preview)."
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1. Find the virtual machine listing by typing in "data science virtual machine" and selecting "Data Science Virtual Machine - Windows 2019."
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1. Select the **Create** button at the bottom.
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