In this chapter, we learned how to process data using data table operations and built some simple R plots for exploratory data analysis. We learned how to use decision trees to find useful insights and build machine learning models (random forest) to perform predictions. We saw how to change the parameters of a model and how to validate it.

The next three chapters show the steps introduced in this chapter in detail. Chapter 4, Step 1 - Data Exploration and Feature Engineering, shows the first step of machine learning that consists of data exploration and feature engineering, in depth.