Davide Pastorello

(Author)

Concise Guide to Quantum Machine Learning (2023)Hardcover - 2023, 17 December 2022

Concise Guide to Quantum Machine Learning (2023)
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Part of Series
Machine Learning: Foundations, Methodologies, and Applications
Print Length
138 pages
Language
English
Publisher
Springer
Date Published
17 Dec 2022
ISBN-10
9811968969
ISBN-13
9789811968969

Description

This book offers a brief but effective introduction to quantum machine learning (QML). QML is not merely a translation of classical machine learning techniques into the language of quantum computing, but rather a new approach to data representation and processing. Accordingly, the content is not divided into a "classical part" that describes standard machine learning schemes and a "quantum part" that addresses their quantum counterparts. Instead, to immerse the reader in the quantum realm from the outset, the book starts from fundamental notions of quantum mechanics and quantum computing. Avoiding unnecessary details, it presents the concepts and mathematical tools that are essential for the required quantum formalism. In turn, it reviews those quantum algorithms most relevant to machine learning. Later chapters highlight the latest advances in this field and discuss the most promising directions for future research.

To gain the most from this book, a basic grasp of statistics and linear algebra is sufficient; no previous experience with quantum computing or machine learning is needed. The book is aimed at researchers and students with no background in quantum physics and is also suitable for physicists looking to enter the field of QML.

Product Details

Author:
Davide Pastorello
Book Edition:
2023
Book Format:
Hardcover
Country of Origin:
NL
Date Published:
17 December 2022
Dimensions:
25.4 x 17.78 x 0.97 cm
ISBN-10:
9811968969
ISBN-13:
9789811968969
Language:
English
Location:
Singapore
Pages:
138
Publisher:
Weight:
480.81 gm

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