March 2023
Intermediate to advanced
680 pages
13h 44m
English
book
A Practical Guide to Quantum Machine Learning and Quantum Optimization
by Elías F. Combarro, Samuel González-Castillo
Overview
This book, "A Practical Guide to Quantum Machine Learning and Quantum Optimization", provides a hands-on introduction to the key modern quantum algorithms in optimization and machine learning. With minimal mathematical prerequisites, you will learn to implement these algorithms on both quantum simulators and actual quantum computers.
What this Book will help me do
- Understand the principles of quantum computing and quantum algorithms.
- Learn how to model and solve optimization problems using QUBO and Ising forms.
- Master techniques like quantum annealing, QAOA, and VQE.
- Gain skills in implementing quantum machine learning models, including SVMs and GANs.
- Become proficient with frameworks such as Qiskit, PennyLane, and D-Wave Leap.
Author(s)
The authors, Elías F. Combarro Fernández-Combarro Álvarez and Samuel González Castillo, are established experts in quantum computing and optimization. They bring their academic and research backgrounds to this book, providing an accessible yet comprehensive resource with practical examples and clear explanations.
Who is it for?
This book is best suited for professionals in fields like computer science, engineering, physics, and mathematics. Readers should have a basic understanding of linear algebra and programming, for instance, in Python. If you're looking to start applying quantum algorithms to optimization and machine learning problems, this book is an excellent resource.
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