In this chapter, we have covered two stages in the predictive analytics process: Problem understanding and definition and Data collection and preparation. We learned about important considerations for understanding the problem and proposing the solution; we also introduced the concepts of regression tasks and classification tasks. We got our hands dirty with a couple of datasets that we will continue within the following chapters, and in going through the second phase, Data collection and preparation, with these datasets, we introduce important concepts such as one-hot encoding, outliers, missing values, collinearity, and feature engineering. In addition, we got to practice how to use pandas for loading, exploring, transforming, and preparing a dataset to continue with the next stages of the predictive analytics process.
In the next chapter, we will study the goals of...