What is Feature Engineering?

Approach: Describe creating new features from raw data to improve model performance.

The process of using domain knowledge to create features that make machine learning algorithms work better. It includes transformation, scaling, encoding categorical variables, and creating interaction terms.

Follow-up: Why is it often considered more important than the algorithm choice?

Key concepts: domain knowledge, one-hot encoding, scaling.