PCA like a Mathematician

Principal Component Analysis, or PCA, is a fundamental dimensionality reduction technique using in Machine Learning. The general goal is to transform a -dimensional problem into a -dimensional one, where is smaller than . This can be used, for instance, to plot large dimensional data on a 2D or 3D plot, or to reduce the number Continue reading PCA like a Mathematician