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Principal Component Analysis

Packages used:

Numpy Pandas Sklearn Matplotlib

Brief explanation:

An algorithm that reduces the dimensionality of a data set to a lower-dimensional linear subspace by linear projection in such a way that the reconstruction error made by the linear projection is as low as possible.

The implementation of Principal Component Analysis on Face Recognition is also present in the repository.