  Quantum systems have an exponentially large degree of freedom in the number
of particles and hence provide a rich dynamics that could not be simulated on
conventional computers. Quantum reservoir computing is an approach to use such
a complex and rich dynamics on the quantum systems as it is for temporal
machine learning. In this chapter, we explain quantum reservoir computing and
related approaches, quantum extreme learning machine and quantum circuit
learning, starting from a pedagogical introduction to quantum mechanics and
machine learning. All these quantum machine learning approaches are
experimentally feasible and effective on the state-of-the-art quantum devices.
