Computational Thinking, Python, Linear Algebra, Linear Regression, Jupyter Notebook.
scipy.linalg.cholesky(AtA) np.set_printoptions(suppress=True, precision=4) R np.linalg.norm(AtA - R.T @ R) 4.5140158187158533e-16 w = scipy.linalg.solve_triangular(R, Atb, lower=False, trans='T') It’s always good to check that our result is what we expect it to be: (in case we entered the wrong