  A classification of multipartite entanglement in qubit systems is introduced
for pure and mixed states. The classification is based on the robustness of the
said entanglement against partial trace operation. Then we use current machine
learning and deep learning techniques to automatically classify a random state
of two, three and four qubits without the need to compute the amount of the
different types of entanglement in each run; rather this is done only in the
learning process. The technique shows high, near perfect, accuracy in the case
of pure states. As expected, this accuracy drops, more or less, when dealing
with mixed states and when increasing the number of parties involved.
