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Principal Component Analysis (PCA): Explained Step-by-Step | Built In
Principal component analysis (PCA) is a technique that reduces the number of variables in a data set while preserving key patterns and trends. It simplifies complex data, making analysis and machine learning models more efficient and easier to interpret.
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