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Publicado por Packt Publishing 12/31/2024, 2024
ISBN 10: 1836209614 ISBN 13: 9781836209614
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Añadir al carritoPaperback or Softback. Condición: New. Quantum Machine Learning and Optimisation in Finance - Second Edition: Drive financial innovation with quantum-powered algorithms and optimisation str. Book.
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Añadir al carritoPaperback. Condición: New. In this book, you'll learn the principles of quantum computing and machine learning, focusing on practical algorithms for NISQ systems. This book shows you how to leverage hybrid quantum-classical approaches to solve real-world financial challenges.
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Publicado por Packt Publishing 2022-10, 2022
ISBN 10: 1801813574 ISBN 13: 9781801813570
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ISBN 10: 1836209614 ISBN 13: 9781836209614
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Añadir al carritoPaperback. Condición: New. In this book, you'll learn the principles of quantum computing and machine learning, focusing on practical algorithms for NISQ systems. This book shows you how to leverage hybrid quantum-classical approaches to solve real-world financial challenges.
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ISBN 10: 1801813574 ISBN 13: 9781801813570
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ISBN 10: 1836209614 ISBN 13: 9781836209614
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ISBN 10: 1801813574 ISBN 13: 9781801813570
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Añadir al carritoCondición: New. Print on Demand pp. 310.
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Publicado por Packt Publishing Limited, 2022
ISBN 10: 1801813574 ISBN 13: 9781801813570
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Get a detailed introduction to quantum computing and quantum machine learning, with a focus on finance-related applicationsKey Features: Find out how quantum algorithms enhance financial modeling and decision-making Improve your knowledge of the variety of quantum machine learning and optimisation algorithms Look into practical near-term applications for tackling real-world financial challenges Purchase of the print or Kindle book includes a free PDF Elektronisches BuchBook Description:As quantum machine learning (QML) continues to evolve, many professionals struggle to apply its powerful algorithms to real-world problems using noisy intermediate-scale quantum (NISQ) hardware. This book bridges that gap by focusing on hands-on QML applications tailored to NISQ systems, moving beyond the traditional textbook approaches that explore standard algorithms like Shor's and Grover's, which lie beyond current NISQ capabilities.You'll get to grips with major QML algorithms that have been widely studied for their transformative potential in finance and learn hybrid quantum-classical computational protocols, the most effective way to leverage quantum and classical computing systems together.The authors, Antoine Jacquier, a distinguished researcher in quantum computing and stochastic analysis, and Oleksiy Kondratyev, a Quant of the Year awardee with over 20 years in quantitative finance, offer a hardware-agnostic perspective. They present a balanced view of both analog and digital quantum computers, delving into the fundamental characteristics of the algorithms while highlighting the practical limitations of today's quantum hardware.By the end of this quantum book, you'll have a deeper understanding of the significance of quantum computing in finance and the skills needed to apply QML to solve complex challenges, driving innovation in your work.What You Will Learn: Familiarize yourself with analog and digital quantum computing principles and methods Explore solutions to NP-hard combinatorial optimisation problems using quantum annealers Build and train quantum neural networks for classification and market generation Discover how to leverage quantum feature maps for enhanced data representation Work with variational algorithms to optimise quantum processes Implement symmetric encryption techniques on a quantum computerWho this book is for:This book is for academic researchers, STEM students, finance professionals in quantitative finance, and AI/ML experts. No prior knowledge of quantum mechanics is needed. Mathematical concepts are rigorously presented, but the emphasis is on understanding the fundamental properties of models and algorithms, making them accessible to a broader audience. With its deep coverage of QML applications for solving real-world financial challenges, this guide is an essential resource for anyone interested in finance and quantum computing.Table of Contents The Principles of Quantum Mechanics Adiabatic Quantum Computing Quadratic Unconstrained Binary Optimisation Quantum Boosting Quantum Boltzmann Machine Qubits and Quantum Logic Gates Parameterised Quantum Circuits and Data Encoding Quantum Neural Network Quantum Circuit Born Machine Variational Quantum Eigensolver Quantum Approximate Optimisation Algorithm Quantum Kernels and Quantum Two-Sample Test The Power of Parameterised Quantum Circuits Advanced QML Models Beyond NISQ.
Librería: preigu, Osnabrück, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. Quantum Machine Learning and Optimisation in Finance - Second Edition | Drive financial innovation with quantum-powered algorithms and optimisation strategies | Antoine Jacquier (u. a.) | Taschenbuch | Englisch | 2024 | Packt Publishing | EAN 9781836209614 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Librería: preigu, Osnabrück, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. Quantum Machine Learning and Optimisation in Finance | On the Road to Quantum Advantage | Antoine Jacquier (u. a.) | Taschenbuch | Englisch | 2022 | Packt Publishing | EAN 9781801813570 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 83,50
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Learn the principles of quantum machine learning and how to apply themWhile focus is on financial use cases, all the methods and techniques are transferable to other fieldsPurchase of Print or Kindle includes a free Elektronisches Buch in PDFKey Features: Discover how to solve optimisation problems on quantum computers that can provide a speedup edge over classical methods Use methods of analogue and digital quantum computing to build powerful generative models Create the latest algorithms that work on Noisy Intermediate-Scale Quantum (NISQ) computersBook Description:With recent advances in quantum computing technology, we finally reached the era of Noisy Intermediate-Scale Quantum (NISQ) computing. NISQ-era quantum computers are powerful enough to test quantum computing algorithms and solve hard real-world problems faster than classical hardware.Speedup is so important in financial applications, ranging from analysing huge amounts of customer data to high frequency trading. This is where quantum computing can give you the edge. Quantum Machine Learning and Optimisation in Finance shows you how to create hybrid quantum-classical machine learning and optimisation models that can harness the power of NISQ hardware.This book will take you through the real-world productive applications of quantum computing. The book explores the main quantum computing algorithms implementable on existing NISQ devices and highlights a range of financial applications that can benefit from this new quantum computing paradigm.This book will help you be one of the first in the finance industry to use quantum machine learning models to solve classically hard real-world problems. We may have moved past the point of quantum computing supremacy, but our quest for establishing quantum computing advantage has just begun!What You Will Learn: Train parameterised quantum circuits as generative models that excel on NISQ hardware Solve hard optimisation problems Apply quantum boosting to financial applications Learn how the variational quantum eigensolver and the quantum approximate optimisation algorithms work Analyse the latest algorithms from quantum kernels to quantum semidefinite programming Apply quantum neural networks to credit approvalsWho this book is for:This book is for Quants and developers, data scientists, researchers, and students in quantitative finance. Although the focus is on financial use cases, all the methods and techniques are transferable to other areas.Table of Contents The Principles of Quantum Mechanics Adiabatic Quantum Computing Quadratic Unconstrained Binary Optimisation Quantum Boosting Quantum Boltzmann Machine Qubits and Quantum Logic Gates Parameterised Quantum Circuits and Data Encoding Quantum Neural Network Quantum Circuit Born Machine Variational Quantum Eigensolver Quantum Approximate Optimisation Algorithm The Power of Parameterised Quantum Circuits Looking Ahead Bibliography.