000			01541 a2200241 4500
005			20190923145441.0
008			190920b xxu||||| |||| 00| 0 eng d
020			_a9783319964232
040			_cIIT Kanpur
041			_aeng
082			_a006.31 _bSch77s
100			_aSchuld, Maria
245			_aSupervised learning with quantum computers _cMaria Schuld and Francesco Petruccione
260			_bSpringer _c2018 _aSwitzerland
300			_axiii, 287p
440			_aQuantum science and technology
490			_a/ edited by Raymond Laflamme
520			_aQuantum 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.
650			_aPattern recognition
650			_aQuantum physics (quantum mechanics &​ quantum field theory)
700			_aPetruccione, F.
942			_cBK
999			_c560737 _d560737