Quantum Machine Learning and Optimisation in Finance
- Paperback: 442 pages
- Publisher: WOW! eBook (October 31, 2022)
- Language: English
- ISBN-10: 1801813574
- ISBN-13: 978-1801813570
Quantum Machine Learning and Optimisation in Finance: Learn the principles of quantum machine learning and how to apply them in finance
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.
- 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 approvals
This Quantum Machine Learning and Optimisation in Finance 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!