What is feature engineering and why is it important in machine learning?

Feature engineering involves creating new features from raw data or transforming existing ones to improve the performance of machine learning models. It is important because the quality of features directly impacts model performance. Examples include normalization, encoding categorical variables, and creating interaction terms between features.