Understanding the features that we are working with is step zero of feature engineering. If we cannot understand the data given to us, we will never hope to fix, create, and utilize features in order to create well-performing, machine-learning pipelines. In this chapter, we were able to recognize, and extract the levels of data from our datasets and use that information to create useful and meaningful visuals that shine new lights on our data.
In the next chapter, we will use all of this new-found knowledge of the levels of data to start improving our features, and we will start to use machine-learning to effectively measure the impact of our feature engineering pipelines.
