QR decomposition, also known as QR factorization, is a method for decomposing a matrix into the product of an orthogonal matrix and an upper-triangular matrix. It is a useful tool for solving systems of linear equations, computing the inverse of a matrix, and computing the singular value decomposition (SVD) of a matrix. In this blog… Continue reading How to do QR Decomposition in Python with Numpy