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Combining the insight of quantum chemistry with the power of machine learning could revolutionize the field of chemistry, so the huge growth of interest in this area is unsurprising. However, for non-specialists it can be difficult to know where to start in learning about the possibilities and tools available. Quantum Chemistry in the Age of Machine Learning covers this exciting field in detail, ranging from the basic concepts to comprehensive methodological details. Such an approach helps readers get a quick overview of existing techniques as well as providing an opportunity to learn the intricacies and inner working of the state-of-the-art methods. The book describes underlying concepts of supervised and unsupervised learning applied to solve quantum chemical problems, covering the broad field of special- and general-purpose machine learning potentials, active learning, learning of various quantum chemical properties, ?-learning, improving the Hamiltonian, learning the wavefunction, and analysis of Big Data. Drawing on the experience of an expert team of contributors, Quantum Chemistry in the Age of Machine Learning is a valuable guide to this exciting area for both aspiring beginners and specialists in the field. Compiles advances of machine learning in quantum chemistry across different areas into a single resource Provides insight into the underlying concepts of machine learning techniques relevant to quantum chemistry Describes in detail the current state-of-the-art machine learning-based methods in quantum chemistry