Building a Model with R

The last part of this book is about modeling data. It has been a long learning journey so far. We started with the fundamentals of data wrangling while covering the concepts that surround the matter and going through techniques to munge each type of data. During practical projects, we had the opportunity to wrangle entire datasets, showing some transformations. In the previous part, we worked with plenty of material regarding data visualization while going over one of the most complete libraries for visualization.

Now, it is time to put all our knowledge to the test and work on a final project. This will involve end-to-end work, from loading the dataset into RStudio to deploying it in a production environment using Shiny, where anyone can interact with the application.

This project will be built during these last two chapters in Part 4. Let’s get to work.

We will be covering the following main topics:

• Machine learning concepts
• Understanding...