We use machine learning techniques to develop tests to separate types of quantum entanglement. In particular, I will describe an artificial neural network model we used to learn membership on certain algebraic varieties. Our results show that it is possible to learn membership on varieties (like a hyperdeterminantal hypersurface) where traditional interpolation methods would be infeasible.    This is joint work with Hamza Jaffali who works at ColibrITD, a quantum information startup in Paris, France.