Maria Schuld – författare

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6 produkter

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6 produkter

Supervised Learning with Quantum Computers
AvMaria Schuld,Francesco Petruccione
Häftad, Engelska, 2019
1 947 kr
Skickas inom 10-15 vardagar
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.
Machine Learning with Quantum Computers
AvMaria Schuld,Francesco Petruccione
Inbunden, Engelska, 2021
1 408 kr
Skickas inom 10-15 vardagar
This book offers an introduction into quantum machine learning research, covering approaches that range from "near-term" to fault-tolerant quantum machine learning algorithms, and from theoretical to practical techniques that help us understand how quantum computers can learn from data. Among the topics discussed are parameterized quantum circuits, hybrid optimization, data encoding, quantum feature maps and kernel methods, quantum learning theory, as well as quantum neural networks. The book aims at an audience of computer scientists and physicists at the graduate level onwards. The second edition extends the material beyond supervised learning and puts a special focus on the developments in near-term quantum machine learning seen over the past few years.
Machine Learning with Quantum Computers
AvFrancesco Petruccione,Maria Schuld
E-bok
Engelska, 2021
1 728 kr
Läs direkt efter köp
This book offers an introduction into quantum machine learning research, covering approaches that range from "near-term" to fault-tolerant quantum machine learning algorithms, and from theoretical to practical techniques that help us understand how quantum computers can learn from data. Among the topics discussed are parameterized quantum circuits, hybrid optimization, data encoding, quantum feature maps and kernel methods, quantum learning theory, as well as quantum neural networks. The book aims at an audience of computer scientists and physicists at the graduate level onwards.
The second edition extends the material beyond supervised learning and puts a special focus on the developments in near-term quantum machine learning seen over the past few years.
Machine Learning with Quantum Computers
AvMaria Schuld,Francesco Petruccione
Häftad, Engelska, 2022
1 408 kr
Skickas inom 10-15 vardagar
This book offers an introduction into quantum machine learning research, covering approaches that range from "near-term" to fault-tolerant quantum machine learning algorithms, and from theoretical to practical techniques that help us understand how quantum computers can learn from data. Among the topics discussed are parameterized quantum circuits, hybrid optimization, data encoding, quantum feature maps and kernel methods, quantum learning theory, as well as quantum neural networks. The book aims at an audience of computer scientists and physicists at the graduate level onwards. The second edition extends the material beyond supervised learning and puts a special focus on the developments in near-term quantum machine learning seen over the past few years.
Supervised Learning with Quantum Computers
AvMaria Schuld,Francesco Petruccione
Inbunden, Engelska, 2018
1 947 kr
Skickas inom 10-15 vardagar
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.
Supervised Learning with Quantum Computers
AvFrancesco Petruccione,Maria Schuld
E-bok
Engelska, 2018
2 517 kr
Läs direkt efter köp
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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Maria Schuld – författare

Supervised Learning with Quantum Computers

Machine Learning with Quantum Computers

Machine Learning with Quantum Computers

Machine Learning with Quantum Computers

Supervised Learning with Quantum Computers

Supervised Learning with Quantum Computers

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