Supervised Learning with Quantum Computers (Hardcover, 1st ed. 2018)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Quantum Science and Technology
Release date:	September 2018
First published:	2018
Authors:	Maria Schuld • Francesco Petruccione
Dimensions:	235 x 155 x 26mm (L x W x T)
Format:	Hardcover
Pages:	287
Edition:	1st ed. 2018
ISBN-13:	978-3-319-96423-2
Categories:	Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Computing & IT > Applications of computing > Pattern recognition Books > Science & Mathematics > Mathematics > Applied mathematics > General Books > Science & Mathematics > Physics > Quantum physics (quantum mechanics) > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics Promotions
LSN:	3-319-96423-2
Barcode:	9783319964232

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