Matrix Eigendecomposition
Eigendecomposition is the factorization of a matrix, where the matrix is represented by its eigenvalues and eigenvectors. Suppose we have the matrix \(A\) whose dimension is \(n \times n\), \(A\)...
Singular Value Decomposition
As described by Professor Gilbert Strang from the Massachusetts Institute of Technology in this video, every \(m \times n\) matrix \(A\) can be factored as follows. \[A = U \Sigma...
Principal Component Analysis
Principal component analysis is the process of computing the principal components for multivariate data points. The principal components can be used to help simplify the analysis by reducing the number...
Bayesian Statistics and Naive Bayes Classifiers
Bayesian statistics is an approach in statistics where probability is interpreted as a degree in belief in an event. The probability of event \(A\) happening given \(B\) is true can...
Moore-Penrose Inverse
I got introduced to the Moore-Penrose inverse, also known as pseudoinverse or generalized inverse, in an internal sharing session at my company’s engineering meeting. Since I haven’t really heard about...