Principal Component, Data Science, Dimensionality Reduction, Machine Learning.
formula: This is the matrix we need to find the eigenvectors and eigenvalues. Where the eigenvectors will be the directions (principal components) and eigenvalues will represent the amount of variance of each principal component. Then we need to reorganise the eigenvectors. The higher eigenvalues