Data normalization

Min-max: x' = (x−min)/(max−min) — scales to [0,1], outlier-sensitive. Z-score: x' = (x−μ)/σ — how many σ from the mean; good for normal distributions, outliers visible (|z|>3). Before ML normalization, save min/max/μ/σ — you'll need them to invert.