RStudio has collaborated with Azure ML to make RStudio Workbench available on the Azure ML environment. The president, Tareef Kawaf, briefed, “RStudio is very pleased to work with the Azure Machine Learning team on this release, as we collaborate to make it easier for organizations to move their open-source data science workloads to the cloud.”
RStudio Workbench offers an IDE (integrated development environment) for the R programming language. It provides open-source and ready-to-use professional software for research, technical communication, and data science.
On the other hand, Azure ML environments provide an encapsulation where users can train their ML scripts. They define the Python packages, software settings, and environment variables around your scoring scripts.
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With Rstudio conjugating with the Azure ML environment, users can conveniently access, analyze, and develop better results. This offering allows one to begin as a single-user instance and effortlessly integrate RStudio benefits into analytics work within the Azure ML environment.
This will be possible with all three broad categories of environments-curated, user-managed and system-managed. Azure ML provides curated environments by default. To access RStudio in user-managed environments, one must set up and manually install all required packages. Lastly, conda will manage all python-based environments after being specified in system-managed environments.
The partnership allows one to use the following functions of RStudio: preferred IDE (VSCode/Jupyter Notebook/RStudio), open multiple Python sessions, access different versions of Python (and R), make use of pre-installed packages and run several scripts in the background.
All of the functions of RStudio Workbench, as mentioned above, are availed within the Azure Platform.
