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Build an Application with Shiny in R
We have finally reached the last chapter. We have learned so much during this book, and we have been able to consolidate our new knowledge with the machine learning project we created in the last chapter. Now, it is time to put that model in production, making it available for the final user.
Putting a model into production is nothing more than taking it from the environment where it was created and trained, usually an internal environment in a company or even a data scientist’s local machine, and making it available in an application, serving the purpose it was created for.
In this project, putting the model into production entails creating a web app with the Shiny library, embedding the model into it, ...
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