Machine learningMachine learning and artificial intelligenceArtificial intelligence have risen in popularity, capable of performing a wide variety of tasks with great accuracy. In classical domains, machine learningMachine learning models are restricted by the computational resources required, often taking days to train. Quantum computingQuantum computing provides a possible avenue to accelerate these machine learningMachine learning models in diverse application domains. In this chapter, we analyze the state of quantum machine learningMachine learning today and compare the machine learning models between classical and quantum domains. Specifically, we discuss the four possible intersections of classical and quantum domains based on data and models, including classical–classical (classical model processing classical data), classical–quantum (classical model processing quantum data), quantum–classical (quantum model processing classical data), and quantum–quantum (quantum model processing quantum data).