Linear Algebra with Numpy: All You Need to Know

Lots of commands in Numpy for linear algebra are shown in this video, including addition and subtraction of matrices, matrix and element-wise products, norm, sort, max and min, argmax and argmin, argwhere, sum and prod, mean, dot and cross product, squeeze, determinant, inverse, flatten, reshape, transpose, pseudo-inverse, eigenvalues, singular value decomposition, and special matrices (zeros, ones, identity, diagonal, random).