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How does PCA reduce the dimensionality of data while preserving most of its variance? What mathematical technique is used to find the principal components in PCA? What are eigenvalues and eigenvectors in the context of PCA? How are principal components ranked in terms of capturing variance in the data? What are the advantages of using PCA for ...
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