Computational Thinking, Linear Algebra, Linear Regression, Python, Jupyter Notebook.
@vectorize def vec_numba(x,y): x = x*2 - ( y * 55 ) y = x + y*2 z = x + y + 99 return z * ( z - .88 ) np.allclose(vec_numba(x,y), proc_numba(x,y,z), atol=1e-4 ) True %timeit vec_numba(x,y) 5.82 µs ± 14.4 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each) Numba is amazing. Look how fast