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What is Dimensionality Reduction?

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Dimensionality Reduction is the process of reducing the number of variables or features in a dataset while retaining its essential information. By eliminating irrelevant or redundant features, businesses can simplify data analysis, improve model performance, and reduce computational complexity. Dimensionality Reduction techniques include Principal Component Analysis (PCA) and t-SNE.

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