Machine Learning Server in the Cloud
Machine Learning Server, formerly known as Microsoft R Server, is a broadly deployed enterprise-class analytics platform for R and Python on-premises computing.
It's also available in the cloud on Azure virtual machines (VM), and through Azure services that have integrated the R and Python libraries. This article explains your options for accessing Machine Learning Server functionality in Azure.
Azure virtual machines with Machine Learning Server
You can provision an Azure virtual machine, running either a Windows or Linux operating system, that already has Machine Learning Server with both R and Python support. In the Azure portal, you can search for "machine learning server" to see your options for the most current release. The following screenshot happens to show version 9.3. Other versions might be available but this gives you an idea of what to expect.
Perhaps the easiest way to provision the VM is one-click install using an Resource Manager template. If you have an Azure subscription, you can use an Resource Manager template that performs the following tasks: provisions a virtual machine, installs Machine Learning Server, opens port 12800, and configures the server for operationalization.
Follow these links to get started:
Other options include:
Machine Learning Server as preconfigured Azure virtual machine on Linux or Windows. Choose this approach if you want to build your VM manually. The VM image provides the core engine but operationalization is not configured. For instructions on how to add operationalization, see Operationalize analytics with Machine Learning Server.
Data science VM
Azure also offers a data science VM that has a full toolset, where the R and Python packages in Machine Learning Server are just one component. For more information, see What's included in the Data Science VM.
The following Azure services include R and Python packages: