Mathematics
Principal Component Analysis for Dimension Reduction
Quick fact
PCA was invented in 1901 by Karl Pearson, but it only became widely used after computers made the calculations practical.
Why this is interesting
Imagine you have a dataset with hundreds of measurements for each item, but you suspect only a few underlying trends matter. How can you simplify it without losing the essence?