In machine learning and data analysis, feature engineering is a critical step. It describes the method of choosing, modifying, and producing fresh features (input variables or attributes) from unprocessed data that can be utilized to enhance the functionality of machine learning models. In order for the model to make correct predictions or classifications, feature engineering aims to provide it with the most pertinent and instructive data possible.