12.1 Introduction12.2 Quantum cryptography12.2.1 Cryptography’s advantages12.2.2 Cryptography’s various forms12.2.3 Cryptography using elliptical curves12.2.4 Visual cryptography12.2.5 Financial cryptography12.2.6 Cryptography in games12.3 Classical machine learning12.3.1 Data-driven learning and interaction-driven learning12.3.2 Supervised learning12.3.3 Unsupervised learning12.3.4 Reinforcement learning12.3.5 Machine learning models12.3.6 Support vector machines for supervised learning12.4 Application quantum computing in ad hoc networks12.5 Computational learning theories12.5.1 Quantum machine learning12.5.2 Quantum machine learning algorithms implementation12.5.3 Quantum clustering [31]12.5.4 The quantum neural network (QNN) [32]12.5.5 Quantum decision tree [33]12.6 Machine learning is used in learning and renormalization procedures12.6.1 Quantum support vector machine12.6.2 Quantum classifier12.6.3 Quantum computing, quantum learning, and quantum artificial intelligence12.6.4 Classical neural networks12.7 Conclusions