The purpose of this project is to discuss a popular approach to face recognition called Eigenfaces.

The idea of Eigenfaces is to construct a low-dimensional linear subspace that contains most of the face images possible with small errors. The essence of eigenfaces is an unsupervised dimensionality reduction algorithm called Principal Components Analysis (PCA) that we use to reduce the dimensionality of images into something smaller.

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Language: Python