Computational Thinking, Linear Algebra, Python, Jupyter Notebook, Math.
columns Q = np.zeros([m,n+1]) #, dtype=np.float64) # 1st col of Q is a random column with unit norm b = np.random.rand(m) Q[:,0] = b / np.linalg.norm(b) for j in range(n): v = A @ Q[:,j] for i in range(j+1): #This comes from the formula for projection of v onto q. #Since columns q are orthonormal,