Math, Matrix, Linear Algebra, Linear Regression Python, Linear Regression.
first k terms, the pseudoinverse is: In our singular case, given by Ms, the singular values, as computed by NumPy are: 6.99811874e+00 3.32059242e+00 5.73361908e-17 The last singular value is essentially zero. Taking only the first two terms we get a pseudoinverse of the matrix. How does this help