The potential for quantum machine learning is starting to shift from theory to well-contained industrial trials. It is most likely to be useful in situations where data for industry is not abundant, is hard to tag, high dimensional, physically structured, or is associated with challenging optimization problems. This chapter reviews some of the major architectures relevant to current industrial applications of artificial intelligence that are currently applicable to quantum computing: quantum ker