Concise Guide to Quantum Machine Learning [E-Book] / by Davide Pastorello.
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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Full text |
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Personal Name(s): | Pastorello, Davide, author |
Edition: |
1st edition 2023. |
Imprint: |
Singapore :
Springer,
2023
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Physical Description: |
X, 138 pages 12 illustrations, 5 illustrations in color (online resource) |
Note: |
englisch |
ISBN: |
9789811968976 |
DOI: |
10.1007/978-981-19-6897-6 |
Series Title: |
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Machine Learning: Foundations, Methodologies, and Applications
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Subject (LOC): |
- 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.