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Quantum Science and Technology Ser.: Machine Learning with Quantum Computers by Francesco Petruccione and Maria Schuld (2021, Hardcover)
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About this product
Product Identifiers
PublisherSpringer International Publishing A&G
ISBN-103030830977
ISBN-139783030830977
eBay Product ID (ePID)8050398170
Product Key Features
Number of PagesXiv, 312 Pages
Publication NameMachine Learning with Quantum Computers
LanguageEnglish
Publication Year2021
SubjectIntelligence (Ai) & Semantics, Probability & Statistics / General
TypeTextbook
AuthorFrancesco Petruccione, Maria Schuld
Subject AreaMathematics, Computers
SeriesQuantum Science and Technology Ser.
FormatHardcover
Dimensions
Item Weight23.2 Oz
Item Length9.3 in
Item Width6.1 in
Additional Product Features
Edition Number2
Number of Volumes1 vol.
IllustratedYes
Table Of ContentChapter 1. Introduction.- Chapter 2. Machine Learning.- Chapter 3. Quantum Computing.- Chapter 4. Representing Data on a Quantum Computer.- Chapter 5. Variational Circuits as Machine Learning Models.- Chapter 6. Quantum Models as Kernel Methods.- Chapter 7. Fault-Tolerant Quantum Machine Learning.- Chapter 8. Approaches Based on the Ising Model.- Chapter 9. Potential Quantum Advantages.
SynopsisThis 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.
LC Classification NumberQA76.889
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