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Concise Guide to Quantum Machine Learning

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 div...

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Bibliografski detalji
Glavni autor: Pastorello, Davide (Autor)
Autor kompanije: SpringerLink (Online service)
Format: Elektronički e-knjiga
Jezik:engleski
Izdano: Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
Izdanje:1st ed. 2023.
Serija:Machine Learning: Foundations, Methodologies, and Applications,
Teme:
Artificial intelligence.
Machine learning.
Quantum computers.
Artificial Intelligence.
Machine Learning.
Quantum Computing.
Online pristup:https://doi.org/10.1007/978-981-19-6897-6
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Sadržaj:
  • Chapter 1: Introduction
  • Chapter 2: Basics of Quantum Mechanics
  • Chapter 3: Basics of Quantum Computing
  • Chapter 4: Relevant Quantum Algorithms
  • Chapter 5: QML Toolkit
  • Chapter 6: Quantum Clustering
  • Chapter 7: Quantum Classification
  • Chapter 8: Quantum Pattern Recognition
  • Chapter 9: Quantum Neural Networks
  • Chapter 10: Concluding Remarks.

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