Resources for Building Production-Quality Shiny Applications
Important Links
- RStudio Cloud Workspace: Click to automatically join the RStudio Cloud Project for this workshop
- RStudio Connect: rsc.training.rstudio.com
- GitHub Discussion Board: github.com/rstudio-conf-2022/shiny-prod-apps/discussions
- Collaborate Google Doc: bitl.y/shinynotes
- Discord channel:
#building-production-quality-shiny-applications
Workshop Data Guide
Throughout this workshop, each of the exercises and live-coding sessions will utilize data from the Metropolitan Museum of Art, otherwise known as the MET, located in New York, United States. The museum offers data sets associated with the art and objects hosted in the museum via their public API. Additional metadata associated with each image of the art piece or object was also generated using the Google Vision API, and in particular the following methods:
- Label detection: Detect and extract information about entities in an image across a broad group of categories.
- Object annotation: Detect and extract information about multiple objects in an image.
- Image properties: Detect color attributes of an image.
- Crop hints: Obtain vertices of a cropped region for an image.