Machine learning models rely nous-mêmes numerical representations of data to identify parfait and make predictions. However, raw data often contains noise, irrelevant récente, or missing values that can degrade model assignation. Feature engineering in ML helps in:In a fraud detection system, adding a feature like "average alliance amount per day