Summary

We have reached the end of this book, and we closed it by learning about a fantastic tool: the Shiny library for R. Shiny is a tool for building interactive applications, enabling R developers to deploy and show their work online.

In this chapter, we learned the basics of the Shiny library, how to get started, and the most common functions, and we then turned our efforts to build an application that wrapped the random forest model trained in the last chapter, enabling it to serve the purpose that it was built for: helping our digital marketing client to have fewer messages going to the spam box.

The project was based on patterns from an open dataset from the UCI repository; therefore, it will not be applicable to any specific emails or any messages, but more specifically to the patterns learned from that dataset, to solve the problem from our hypothetical client, which was our goal.

We ended the chapter by deploying the app online using the ShinyApps.io free version...