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(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2018/09/r-developers-guide-to-azure.html"> Revolutions</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
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<p>If you want to run R in the cloud, you can of course run it in a virtual machine in the cloud provider of your choice. And you can do that in Azure too. But Azure provides seven dedicated services that provide the ability to run R code, and you can learn all about them in the new <a rel="nofollow" href="https://docs.microsoft.com/azure/machine-learning/r-developers-guide?WT.mc_id=Revolutions-blog-davidsmi" target="_blank">R Developer's Guide to Azure</a> at Microsoft Docs. The services include:</p>
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<li><a data-linktype="self-bookmark" rel="nofollow" href="https://docs.microsoft.com/en-us/azure/machine-learning/r-developers-guide?WT.mc_id=Revolutions-blog-davidsmi#data-science-virtual-machine" target="_blank">Data Science Virtual Machine</a>: a customized VM to use as a data science workstation or as a custom compute target. This includes <a data-linktype="external" rel="nofollow" href="https://mran.microsoft.com/open/" target="_blank">Microsoft R Open</a>, <a data-linktype="external" rel="nofollow" href="https://docs.microsoft.com/machine-learning-server/what-is-machine-learning-server" target="_blank">Microsoft Machine Learning Server</a>, and <a rel="nofollow" href="https://docs.microsoft.com/sql/advanced-analytics/?view=sql-server-2017&WT.mc_id=Revolutions-blog-davidsmi" target="_blank">Microsoft ML Services in SQL Server</a>, which can also be run locally.</li>
<li><a data-linktype="self-bookmark" rel="nofollow" href="https://docs.microsoft.com/en-us/azure/machine-learning/r-developers-guide?WT.mc_id=Revolutions-blog-davidsmi#ml-services-on-hdinsight" target="_blank">ML Services on HDInsight</a>: a cluster-based system for running R analyses on large datasets across many nodes.</li>
<li><a data-linktype="self-bookmark" rel="nofollow" href="https://docs.microsoft.com/en-us/azure/machine-learning/r-developers-guide?WT.mc_id=Revolutions-blog-davidsmi#azure-databricks" target="_blank">Azure Databricks</a>: a collaborative Spark environment that supports R and other languages.</li>
<li><a data-linktype="self-bookmark" rel="nofollow" href="https://docs.microsoft.com/en-us/azure/machine-learning/r-developers-guide?WT.mc_id=Revolutions-blog-davidsmi#azure-machine-learning-studio" target="_blank">Azure Machine Learning Studio</a>: a drag-and-drop app for Azure's machine learning experiments, that supports custom R scripts.</li>
<li><a data-linktype="self-bookmark" rel="nofollow" href="https://docs.microsoft.com/en-us/azure/machine-learning/r-developers-guide?WT.mc_id=Revolutions-blog-davidsmi#azure-batch" target="_blank">Azure Batch</a>: a variety of options for economically running R code across many nodes in a cluster.</li>
<li><a data-linktype="self-bookmark" rel="nofollow" href="https://docs.microsoft.com/en-us/azure/machine-learning/r-developers-guide?WT.mc_id=Revolutions-blog-davidsmi#azure-notebooks" target="_blank">Azure Notebooks</a>: a no-cost (but limited) cloud-based version of Jupyter notebooks.</li>
<li><a data-linktype="self-bookmark" rel="nofollow" href="https://docs.microsoft.com/en-us/azure/machine-learning/r-developers-guide?WT.mc_id=Revolutions-blog-davidsmi#azure-sql-database" target="_blank">Azure SQL Database</a>: to run R scripts inside of the SQL Server database engine.</li>
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<p>Click on the links above for detailed documentation on how to run R in each of these services. Like all Microsoft Docs this guide is hosted in Github, so if you have suggestions for modifications or additions to this document, you can use the &quot;Content Feedback&quot; link to provide suggestions directly in the repository.</p>
<p>Microsoft Docs: <a rel="nofollow" href="https://docs.microsoft.com/azure/machine-learning/r-developers-guide?WT.mc_id=Revolutions-blog-davidsmi" target="_blank">R developer's guide to Azure</a></p>
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