Supervised Learning with Quantum Computers
Softcover reprint of the original 1st ed. 2018
Book Details
Format
Paperback / Softback
Book Series
Quantum Science and Technology
ISBN-10
303007188X
ISBN-13
9783030071882
Edition
Softcover reprint of the original 1st ed. 2018
Publisher
Springer Nature Switzerland AG
Imprint
Springer Nature Switzerland AG
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Jan 3rd, 2019
Print length
287 Pages
Product Classification:
Condensed matter physics (liquid state & solid state physics)Condensed matter physics (liquid state and solid state physics)Quantum physics (quantum mechanics & quantum field theory)Quantum physics (quantum mechanics and quantum field theory)Mathematical / Computational / Theoretical physicsMathematical physicsMaterials scienceMathematical theory of computationArtificial intelligenceArtificial intelligence (AI)Pattern recognition
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Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making.
Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses topics such as data encoding into quantum states, quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine ``quantum learning models''. A special focus lies on supervised learning, and applications for near-term quantum devices.
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