Supervised Learning with Quantum Computers

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Éditeur :

Springer


Collection :

Quantum Science and Technology

Paru le : 2018-08-30

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Description

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.
Pages
287 pages
Collection
Quantum Science and Technology
Parution
2018-08-30
Marque
Springer
EAN papier
9783319964232
EAN PDF
9783319964249

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
28
Taille du fichier
5847 Ko
Prix
179,34 €
EAN EPUB
9783319964249

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
28
Taille du fichier
9994 Ko
Prix
179,34 €