  Machine learning is a fascinating and exciting field within computer science.
Recently, this excitement has been transferred to the quantum information
realm. Currently, all proposals for the quantum version of machine learning
utilize the finite-dimensional substrate of discrete variables. Here we
generalize quantum machine learning to the more complex, but still remarkably
practical, infinite-dimensional systems. We present the critical subroutines of
quantum machine learning algorithms for an all-photonic continuous-variable
quantum computer that achieve an exponential speedup compared to their
equivalent classical counterparts. Finally, we also map out an experimental
implementation which can be used as a blueprint for future photonic
demonstrations.
