What is feature engineering?

Feature engineering is the process of using domain knowledge to extract, transform, and select the most relevant features from raw data to improve the performance of machine learning models. It involves creating new features from existing ones, which can include scaling, encoding categorical variables, handling missing values, and creating interaction terms. Effective feature engineering can significantly impact the accuracy, efficiency, and interpretability of machine learning algorithms.