Feature engineering is the process of selecting, transforming, or creating new features from your raw data to improve the performance of machine learning models. It involves identifying the most relevant information in your data, extracting meaningful patterns, and representing them in a way that helps the model make accurate predictions or classifications. Effective feature engineering can significantly impact the success of a machine learning project by enhancing the model's ability to learn from the data.