Buch, Englisch, 138 Seiten, Paperback, Format (B × H): 178 mm x 254 mm, Gewicht: 293 g
Reihe: Machine Learning: Foundations, Methodologies, and Applications
Buch, Englisch, 138 Seiten, Paperback, Format (B × H): 178 mm x 254 mm, Gewicht: 293 g
Reihe: Machine Learning: Foundations, Methodologies, and Applications
ISBN: 978-981-1968-99-0
Verlag: Springer Nature Singapore
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.
Zielgruppe
Graduate
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
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.