Geo AI Data Science Virtual Machine

By for May 2, 2018

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The Geo AI Data Science Virtual machine (GeoAI DSVM) is a custom Azure VM built on Windows with many popular tools for data science modeling/development, with a focus on Geographic Information System (GIS) tooling.
> **Note:** If you have already deployed this solution, click [here](https://quickstart.azure.ai/track/Deployments?type=geodsvm) to view your deployment. ### Estimated Provisioning Time: 20 Minutes > **STOP, before you proceed to deploy.** By continuing to create and use this extension, you are accepting the Esri [ArcGIS Pro license agreements](http://www.esri.com/legal/software-license) and the [Microsoft Data Science Virtual Machine terms](https://dsvmpublicassets.blob.core.windows.net/publicassets/TermsOfUseDSVM.pdf). > **Important prerequisite:** Please make sure that you enter a unique name for the "Deployment name" and the Geo AI Data Science VM name, during your deployment. This tutorial will allow you to easily provision the Geo AI Data Science Virtual Machine in one easy wizard with the recommended parameters already selected, without using the Azure portal. The [documentation](https://docs.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/geo-ai-dsvm-overview) has a great overview along with the [full list of available tools](https://docs.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/overview). To fully experience the power of the GeoAI DSVM, we recommend walking through our [pixel-level land use classification tutorial](https://github.com/Azure/pixel_level_land_classification). ## Related materials - Geo AI Data Science VM [product page](http://aka.ms/dsvm/GeoAI) and [documentation](http://aka.ms/dsvm/GeoAI/docs) - [Blog post](https://blogs.technet.microsoft.com/machinelearning/2018/03/12/pixel-level-land-cover-classification-using-the-geo-ai-data-science-virtual-machine-and-batch-ai/) on pixel-level landcover classification - Main [AI for Earth](https://www.microsoft.com/en-us/aiforearth) website - [Keynote demo from Microsoft Ignite](https://www.youtube.com/watch?time_continue=1&v=MUqo-lsAKgQ#t=23m46s) - [Publicity video on the Chesapeake Conservancy collaboration with Microsoft](http://chesapeakeconservancy.org/2017/07/10/microsoft-video-features-chesapeake-conservancy/) - [Video clip showing real-time local application of the trained CNTK model through ESRI's ArcGIS software](https://www.youtube.com/watch?v=_iq-_K1OsMA) ## Disclaimer ©2017 Microsoft Corporation. All rights reserved. This information is provided "as-is" and may change without notice. Microsoft makes no warranties, express or implied, with respect to the information provided here. Third party data was used to generate the Solution. You are responsible for respecting the rights of others, including procuring and complying with relevant licenses in order to create similar datasets. ![ ](https://quickstart.azure.ai/track?solutionid=geodsvm)