What is feature engineering in machine learning?

Feature engineering is the process of using domain knowledge to create, transform, or select input variables (features) that help ML models perform better.

Techniques include:
- **Encoding** categorical variables (Label, One-Hot)
- **Scaling** numerical features (MinMax, StandardScaler)
- **Creating new features** from existing ones (age from DOB)
- **Binning** continuous values into categories
- **Polynomial features** for non-linear relationships

Good features often matter more than the choice of algorithm.