[Python] Difference between ways to solve linear algebra equations in NumPy (inv, solve)

solve: first factorizes A using LU decomposition, then solves for xusing forward and backward substitution

inv: uses the same method to compute the inverse of A by solving for A-1 in A·A-1 = I where I is the identity*. The factorization step is exactly the same as above, but it takes more floating point operations to solve for A-1 (an n×n matrix) than for x (an n-long vector).



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