Eigenvectors, Eigenvalue, Data Science, Machine Learning, Principal Component.
contain reduced informational redundancy, giving a truly optimal view of the underlying structure of the data. There are more “statistics-y” ways of understanding PCA. The main idea is to think about finding lines-of-best-fit that minimize the total distance to every sample. This seems a little