by Pablo Duboue – Textualization Software Ltd.

Feature Engineering (FE) is a set of techniques that allows human knowledge and intuitions to be added to a ML solution by controlling the input of raw data during the ML process. There are a number of well-understood methods and transformations that can be applied to the features. This process is better done iteratively, starting from EDA, and performing EA after each iteration. This chapter showcases basic FE operations, allowing a data scientist to decide whether or not to engage in a FE process. The FE operations will be exemplified in a case study about Airbnb price predictions.