Discover the various features that contribute to favoring a particular cereal and the importance of feature engineering in modeling consumer ratings. Uncover the concept of post-hoc feature attribution and its role in interpreting ML model behavior. Join us as we delve into the interpretability of ML models in understanding cereal preferences.