linear algebra linear algebralike matrix multiplicationdecompositionsdeterminantsand other square matrix mathis an important part of any array library unlike some languages like matlabmultiplying two two-dimensional arrays with is an element-wise product instead of matrix dot product as suchthere is function dotboth an array methodand function in the numpy namespacefor matrix multiplicationin [ ] np array([[ ][ ]]in [ ] np array([[ ][- ][ ]]in [ ] out[ ]array([ ] ]]in [ ] out[ ]array([ ]- ] ]]in [ ] dot(yequivalently np dot(xyout[ ]array([ ] ]] matrix product between array and suitably sized array results in arrayin [ ]np dot(xnp ones( )out[ ]array( ]numpy linalg has standard set of matrix decompositions and things like inverse and determinant these are implemented under the hood using the same industry-standard fortran libraries used in other languages like matlab and rsuch as like blaslapackor possibly (depending on your numpy buildthe intel mklin [ ]from numpy linalg import invqr in [ ] randn( in [ ]mat dot(xin [ ]inv(matout[ ]array([ - - - - ][- ][- ][- ][- ]]in [ ]mat dot(inv(mat)linear algebra www it-ebooks info