<p><div><div><div><div data-show-faces="false" data-height="21" data-width="100" data-layout="button_count" data-send="true" data-href="https://www.r-bloggers.com/updated-data-science-virtual-machine-for-windows-gpu-enabled-with-docker-support/"></div></div><div></div></div><div></div></div>
<div>
(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2017/06/dsvm-update.html"> Revolutions</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<div>
<p>The <a rel="nofollow" href="https://azuremarketplace.microsoft.com/en-us/marketplace/apps/microsoft-ads.windows-data-science-vm" target="_blank">Windows edition of the Data Science Virtual Machine</a> (DSVM), the all-in-one virtual machine image with a wide-collection of open-source and Microsoft data science tools, has been <a rel="nofollow" href="https://blogs.technet.microsoft.com/machinelearning/2017/06/06/introducing-the-new-data-science-virtual-machine-on-windows-server-2016/" target="_blank">updated to the Windows Server 2016 platform</a>. This update brings built-in support for Docker containers and GPU-based deep learning. </p>
<p><strong>GPU-based Deep Learning</strong>. While prior editions of the DSVM could access GPU-based capabilities by installing additional components, everything is now configured and ready at launch. The DSVM now includes GPU-enabled builds of popular deep learning frameworks including CNTK, Tensorflow, and MXNET. It also includes Microsoft R Server 9.1, and several machine-learning functions in the <a rel="nofollow" href="https://msdn.microsoft.com/en-us/microsoft-r/microsoftml/microsoftml" target="_blank">MicrosoftML package</a> can also take advantage of GPUs. Note that you will need to use an <a rel="nofollow" href="https://azure.microsoft.com/en-us/pricing/details/virtual-machines/series/" target="_blank">N-series Azure instance</a> to benefit from GPU acceleration, but all of the tools in the DSVM will also work on regular CPU-based instances as well.</p>
<p><a rel="nofollow" href="http://a2.typepad.com/6a0105360ba1c6970c01b8d28ee2f2970c-pi" target="_blank"><img border="0" alt="GPU screenshot" title="GPU screenshot" src="http://a2.typepad.com/6a0105360ba1c6970c01b8d28ee2f2970c-800wi"></a></p>
<p><strong>Docker Containers</strong>. Windows Server 2016 <a rel="nofollow" href="https://docs.microsoft.com/en-us/virtualization/windowscontainers/index" target="_blank">includes Windows Containers,</a> and the DSVM also includes the <a rel="nofollow" href="https://docs.microsoft.com/en-us/virtualization/windowscontainers/manage-docker/configure-docker-daemon" target="_blank">Docker Engine</a>. This means you can easily run Windows containers from Docker Hub or the Azure Container registry. This is limited to Windows-based containers right now, but you can use Linux-based containers on the <a rel="nofollow" href="https://azuremarketplace.microsoft.com/en-us/marketplace/apps/microsoft-ads.linux-data-science-vm-ubuntu" target="_blank">Data Science Virtual Machine for Ubuntu Linux</a>, which likewise supports <a rel="nofollow" href="https://blogs.technet.microsoft.com/machinelearning/2017/04/18/deep-learning-on-the-new-ubuntu-based-data-science-virtual-machine-for-linux/" target="_blank">GPU-enabled deep learning</a>.</p>
<p>It's easy to <a rel="nofollow" href="https://azuremarketplace.microsoft.com/en-us/marketplace/apps/microsoft-ads.windows-data-science-vm" target="_blank">launch a Windows 2016 DSVM on Azure</a>, and the <a rel="nofollow" href="https://docs.microsoft.com/en-us/azure/machine-learning/machine-learning-data-science-virtual-machine-overview" target="_blank">documentation</a> will help you get started using it. (An Azure account is required, but <a rel="nofollow" href="http://azure.com/free" target="_blank">free Azure credits</a> are available to help get you started.) You can find more information about this update at the link below.</p>
<p>Cortana Intelligence and Machine Learning Blog: <a rel="nofollow" href="https://blogs.technet.microsoft.com/machinelearning/2017/06/06/introducing-the-new-data-science-virtual-machine-on-windows-server-2016/%C2%A0" target="_blank">Introducing the new Data Science Virtual Machine on Windows Server 2016</a></p>
</div>
	<p>
<div>
<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="http://blog.revolutionanalytics.com/2017/06/dsvm-update.html"> Revolutions</a></strong>.</div>
<hr>
<a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers.com</a> offers <strong><a rel="nofollow" href="https://feedburner.google.com/fb/a/mailverify?uri=RBloggers">daily e-mail updates</a></strong> about <a rel="nofollow" href="https://www.r-project.org/" title="The R Project for Statistical Computing">R</a> news and <a rel="nofollow" href="https://www.r-bloggers.com/search/tutorial" title="R tutorials">tutorials</a> on topics such as: <a rel="nofollow" href="https://www.r-bloggers.com/search/data%20science" title="Data science">Data science</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/Big%20Data" title="Big Data">Big Data, <a rel="nofollow" href="https://www.r-users.com/" title="R jobs">R jobs</a>, visualization (<a rel="nofollow" href="https://www.r-bloggers.com/search/ggplot2" title="ggplot and ggplot2 tutorials">ggplot2</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/boxplot" title="Boxplots using lattice and ggplot2 tutorials">Boxplots</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/map" title="Maps and gis">maps</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/animation" title="Animation in R">animation</a>), programming (<a rel="nofollow" href="https://www.r-bloggers.com/search/RStudio" title="RStudio IDE for R">RStudio</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/sweave" title="Sweave and literate programming">Sweave</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/LaTeX" title="LaTeX in R">LaTeX</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/SQL" title="SQL and databases">SQL</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/eclipse" title="Eclipse IDE for R">Eclipse</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/git" title="git and github, Version Control System">git</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/hadoop" title="Large data in R using Hadoop">hadoop</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/Web+Scraping" title="Web Scraping of google, facebook, yahoo, twitter and more using R">Web Scraping</a>) statistics (<a rel="nofollow" href="https://www.r-bloggers.com/search/regression" title="Regressions and ANOVA analysis tutorials">regression</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/PCA" title="principal component analysis tutorial">PCA</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/time+series" title="Time series">time series</a>, <a rel="nofollow" href="https://www.r-bloggers.com/search/trading" title="finance trading">trading</a>) and more...
<img width="1" alt="" src="http://feeds.feedburner.com/~r/RBloggers/~4/0xUXE1E3ZRE" height="1"></a></div>