A statistical technique that reduces data dimensionality while preserving key patterns. It transforms correlated variables into fewer uncorrelated components, simplifying visualization and model training. Widely used in finance, genetics, and image compression, it benefits data scientists, analysts, and researchers seeking to uncover hidden structures or speed up algorithms without losing critical information.
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