Computational Thinking, Python, Linear Algebra, Linear Regression, Jupyter Notebook.
df.set_value(name, 'Error', np.abs(1 - coeffs[-1])) df The solution for least squares via the normal equations is unstable in general, although stable for problems with small condition numbers. Low-rank m = 100 n = 10 x = np.random.uniform(-10,10,n) A2 = np.random.uniform(-40,40, [m, int(n/2)]) #