The AzureDSVM (Azure Data Science Virtual Machine) is an R Package for Data Scientists working with the Azure compute platform as a complement to the underlying AzureSMR for controlling Azure Data Science Virtual Machines.
Azure Data Science Virtual Machine (DSVM) is a powerful data science development environment with pre-installed tools and packages that empower data scientists for convenient data wrangling, model building, and service deployment.
The R package of
AzureDSVM aims at offering functions that can be conveniently used by R data scientists for operating and using Azure Data Science Virtual Machine (DSVM) elastically and economically within local R session.
To install the package from github:
Help pages are also provided for all functions within the package. With RStudio for example type AzureDSVM into search when the package is loaded to see a list of functions/help pages or else
Note: The package will work with any open source R Session or with Microsoft R extensions.
- Deployment of a DSVM with customized information such as machine name, machine size (with compute/memory optimized general-purpose CPU, Nvidia K80/M60 GPU, etc.), operating system (Windows Server 2016, Ubunbut 16.04, and CentOS), authentication method (public key based or password based), etc.
- Enjoy all benefits of a Windows/Linux DSVM. E.g., all tools for data science work such as R/Python/Julia programming languages, SQL Server, Visual Studio with RTVS, etc., remote working environment via RStudio Server or Jupyter Notebook interface, and machine learning & artificial intelligence packages such as Microsoft CNTK, MXNet, and XGBoost.
- Execution of R analytics on DSVM(s) with various Microsoft R Server computing contexts such as "local parallel" and "cluster parallel".
- Seamless interaction with remote R Server session with
- Post-deployment installation of extension for customizing system environment, reinstalling/uninstalling software, etc.
- Deployment of a collection of heterogeneous DSVMs for a group of data scientists.
- Scale up DSVM and form them into a cluster for parallel/distributed computation with Microsoft R Server backend.
- Deploy, start, stop, and delete DSVM(s) on demand.
- Monitor data consumption and estimate expense of using DSVM(s) with hourly aggregation granularity.
To get started with this package, see the Vignettes:
- Get started
- Deployment of a single DSVM
- Deployment of multiple DSVMs
- Do computation on a single DSVM or a cluster of DSVMs
- Monitor data consumption and expense spent on using DSVM(s)
- Putting all together
Code of Conduct
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact email@example.com with any additional questions or comments.