The premier IDE for R
RStudio anywhere using a web browser
Put Shiny applications online
Shiny, R Markdown, Tidyverse and more
Do, share, teach and learn data science
An easy way to access R packages
Let us host your Shiny applications
A single home for R & Python Data Science Teams
Scale, develop, and collaborate across R & Python
Easily share your insights
Control and distribute packages
RStudio
RStudio Server
Shiny Server
R Packages
RStudio Cloud
RStudio Public Package Manager
shinyapps.io
RStudio Team
RStudio Workbench
RStudio Connect
RStudio Package Manager
community
R in Insurance
June 28, 2021
An algorithm is only as valuable as its adoption. Speed to value, repeatability, and low-cost solutions can dramatically reduce software and services budgets and free up valuable dollars for other activities. Open-source tools such as Shiny (R) and Flask (Python) have enabled the creation and deployment of data science-based web applications convenient and manageable. In the healthcare data science world, we routinely wrap sophisticated statistical code into such web-based point-and-click solutions. In this talk, you will learn about real-life examples of how one can rapidly operationalize intricate algorithms using web app frameworks.