Description Quantum machine Learning investigates how Quantum Computers can be used for data-driven prediction and decision making.
Maria Schuld is a.
Since 2013 she dedicates her research to the design of Quantum machine Learning algorithms, which she presented at numerous international conferences and in a range of research articles.
Her Master\'s degree was awarded by the Technical University of Berlin and supported through a scholarship of the German Academic Exchange Service (DAAD).
Maria Schuld received her Ph D degree from the University of Kwa Zulu-Natal in South Africa in 2017 as a fellow of the German Academic Foundation.
Francesco Petruccione\'s research focusses on Quantum information and open Quantum systems.
He is the co-author of "The theory of open Quantum systems" (Oxford University Press, 2002) and has published more than 100 papers in refereed journals, adding up to more than 7000 citations.
Since 2004 he is Professor of Theoretical Physics at the University of Kwa Zulu-Natal in Durban, Africa, where in 2007 he was granted a South African Research Chair for Quantum Information Processing and Communication from the National Research Foundation.
About the Author Francesco Petruccione received his Ph D (1988) and "Habilitation" (1994) from the University of Freiburg, Germany.
A special focus lies on Supervised learning, and applications for near-term Quantum devices.
For more advanced readers, the book discusses topics such as data encoding into Quantum states, Quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine Quantum Learning models\'\'.
It aims at providing a starting point for those new to the field, showcasing a toy example of a Quantum machine Learning algorithm and providing a detailed introduction of the two parent disciplines.
The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards.
Description Quantum machine Learning investigates how Quantum Computers can be used for data-driven prediction and decision making
