Machine Learning, Dimensionality Reduction, Eigenvectors, Algorithms, Mathematics.
Principal Component Analysis (PCA) is one of the most fundamental dimensionality reduction techniques in statistics (also one of the oldest). It creates a new co-ordinate system where the axes of this new system (eigenvectors) capture maximum amount of variance in the data. This might be important