Computational Thinking, Linear Algebra, Linear Regression, Python, Jupyter Notebook.
arrays, and can reuse cached data since we’re doing multiple calculations on each array item. # Untype and Unvectorized def proc_python(xx,yy): zz = np.zeros(nobs, dtype='float32') for j in range(nobs): x, y = xx[j], yy[j] x = x*2 - ( y * 55 ) y = x + y*2 z = x + y + 99 z = z * ( z - .88 ) zz[j] =