Machine learning with quantum computers

Machine learning with quantum computers / Maria Schuld, Francesco Petruccione.

This 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. Am...

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Bibliographic Details
Main Authors: Schuld, Maria (Author), Petruccione, F. (Francesco) (Author)
Format: eBook
Language:English
Published: Cham, Switzerland : Springer, 2021.
Edition:Second edition.
Series:Quantum science and technology,
Subjects:
Machine learning.
Quantum computing.
Machine learning
Quantum computing
Online Access:Click for online access
Table of Contents:
  • Introduction
  • Machine learning
  • Quantum computing
  • Representing data on a quantum computer
  • Variational circuits as machine learning models
  • Quantum models as Kernel methods
  • Fault-tolerant quantum machine learning
  • Approaches based on the Ising model
  • Potential quantum advantages.

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