The Data Science Virtual Machine (DSVM) is a customized VM image on Microsoft’s Azure cloud built specifically for doing data science. It has many popular data science and other tools pre-installed and pre-configured to jump-start building intelligent applications for advanced analytics. So instead of you having to create a VM and download and install all these tools which can take many hours, within a matter of minutes you can be up and running.
The DSVM is designed and configured for working with a broad range of usage scenarios. You can scale your environment up or down as your project needs change. You are able to use your preferred language to program data science tasks. You can install other tools and customize the system for your exact needs.
The key scenarios for using the Data Science VM:
- Preconfigured analytics desktop in the cloud
- Data science training and education
- On-demand elastic capacity for large-scale projects
- Short-term experimentation and evaluation
- Deep learning
The DSVM has many popular data science and deep learning tools already installed and configured. It also includes tools that make it easy to work with various Azure data and analytics products. You can explore and build predictive models on large-scale data sets using the Microsoft R Server or using SQL Server 2016 (note that R Server and SQL Server on the DSVM are not licensed for use on production data). A host of other tools from the open source community and from Microsoft are also included, as well as sample code and notebooks. See the full list here and see the latest new and upgraded tools here.
Finally, for Windows users check out Ten things you can do on the Data science Virtual Machine and for Linux users check out Data science on the Linux Data Science Virtual Machine. For more information on how to run specific tools for Windows see Provision the Microsoft Data Science Virtual Machine and for Linux see Provision the Linux Data Science Virtual Machine.