Computational Thinking, Linear Algebra, Linear Regression, Python, Jupyter Notebook.
vectorizing. This avoids large memory allocations, so we have better locality: @jit() def proc_numba(xx,yy,zz): 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] = z return zz z = np.zeros(nobs).astype('float32') np.allclose(