Concise Guide to Quantum Machine Learning

Davide Pastorello is an assistant professor in the Department of Information Engineering and Computer Science at the University of Trento.

• 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.

“The book under review summarises lecture notes presented by the author for the quantum machine learning MSc course at the University of Trento; it is therefore structured in a student-friendly manner, offering support both on the mathematical side (also with the interpretation of quantum mechanics) and on the algorithmic side. ... The book concludes with an extensive, well-curated set of references, which represent an excellent continuation of quantum approaches.” (Irina Ioana Mohorianu, zbMATH 1530.68003, 2024)