Feature Engineering 

Feature Engineering is a machine learning technique that leverages raw data and creates new features to improve the performance and accuracy of the learning models. The key aspects of feature engineering are creation of new features, transformation of features, selection of features, encoding, and handling missing values. Feature engineering is considered more of an art than science as it requires domain knowledge and intuition to check what changes to data can lead to better model predictions. The success of a model depends on feature engineering.