EEMI

Guided Notes

Transform: Scaling & Feature Engineering

Normalization and standardization, storing scaling parameters, and creating new features like GDP per capita.

Why scale features?

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GDP values run into trillions while populations run into millions. Many machine learning algorithms — those based on distances or gradients — let the larger-scale feature dominate simply because its numbers are bigger.

Scaling puts features on comparable ranges. Two common methods:

• Normalization (min-max) — rescales to the range 0 to 1. • Standardization (z-score) — rescales to mean 0 and standard deviation 1.

The terms are sometimes used loosely; check which one is meant.