This project illustrates using RStudio Connect to deploy a data science project featuring:
Scheduled jobs
- Fetching and cleaning data from a continuously updating web source
- Pushing cleaned data to a relational database
- Creating intermediate datasets for subsequent use
Pins
- Serving intermediate datasets and model objects for use in apps, APIs, and other jobs
APIs
- Serving model predictions via HTTP requests
Development and Production Apps
- Exposing model predictions to end-users through Shiny and Dash apps
- Using git-backed deployment to keep a stable version of the application available from the main branch while doing development work on another branch
Private Packages
- Encapsulate re-usable logic in an R package, and distribute with Package Manager
Explore the deployed items below: