Feature engineering is the process of making data more useful for machine learning algorithms.  It involves creating new input features or modifying existing ones to improve a model's performance in making predictions or classifications. The goal of feature engineering is to extract relevant information from raw data and present it in a way that makes it easier for machine learning algorithms to understand and learn from.