Feature engineering is the process of transforming raw data into a format suitable for machine learning models. It involves selecting, manipulating and transforming input data to create new features that can improve model performance. Features are inputs that models use during training and inference to make predictions. By engineering these features, we can increase the ability of models to learn patterns and make accurate predictions