Dimensionality Reduction, Eigenvectors, Eigenvalue, Data Science, Machine Learning.
features (i.e. many columns) say, n. I want to reduce the number of features to say, d (where d<n). The procedure is to find a set of “d” features that best describes the variation in my dataset. Remember, PCA is only good to apply when features seems to be correlated. To truly understand PCA you