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Dimensionality Reduction with Principal Component Analysis

Principal Component Analysis (PCA) is a dimensionality reduction technique, as its name suggest this algorithm reduces the number of dimensions in such a way that it retains the most relevant information, the algorithm uses principal components which have the variance in the data.

April 30, 2019