Quantum Machine Learning introduces the key models, techniques, and practical considerations for applying quantum algorithms to learning and inference tasks, with an emphasis on the interface between quantum and classical computation. Applications and techniques in machine learning are classified according to their “quantumness” to identify plausible candidates for quantum advantage from quantum machine learning.