Skip to content

Latest commit

 

History

History

Principal Component Analysis

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.