Data Science Virtual Machine for Linux

By for February 22, 2017

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Provision the Data Science Virtual Machine for Linux (Ubuntu), a custom virtual machine image pre-installed and configured with a host of popular tools commonly used for data science and machine learning.
> **Note:** If you have already deployed this solution, click [here]( to view your deployment. ### Estimated Provisioning Time: 3 Minutes [![Take a free test drive](]( > **STOP before you proceed to Deploy** You need to accept the Terms of Use of the Data Science Virtual Machine for Linux (Ubuntu) on your Azure Subscription before you deploy this VM the first time by clicking [here]( **This does not apply to free test drive.** The Data Science Virtual machine for Linux (DSVM) is a custom Azure VM built on Ubuntu 16.04 with many popular tools for data science modeling/development, including: * Microsoft R Open * Microsoft R Server Developer Edition * Anaconda Python * JupyterHub, a multiuser Jupyter notebooks server supporting Python and R * Azure tools and libraries to access various Azure services like AzureML, databases, and big data services * ML and Deep learning tools like xgboost and LightGBM * Deep learning tools like CNTK, TensorFlow, Caffe, Caffe2, mxnet, Theano, Torch, and more The documentation has a [full list of available tools]( and [more information]( on the Ubuntu VM. If are wondering about things you can do with the DSVM read the [How-To Guide to the Data Science Virtual Machine for Linux]( ## 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.