Description: Machine Learning with Quantum Computers by Schuld, Maria, ISBN 3030831000, ISBN-13 9783030831004, Like New Used, Free shipping in the US This book offers an introduction into quantum machine learning research, covering approaches that range from "near-term" to fault-tolerant quantum machine learning algorithms, and from theoretical to practical techniques that help us understand how quantum computers can learn from data. Among the topics discussed are parameterized quantum circuits, hybrid optimization, data encoding, quantum feature maps and kernel methods, quantum learning theory, as well as quantum neural networks. Th aims at an audience of computer scientists and physicists at the graduate level onwards. The second edition extends the material beyond supervised learning and puts a special focus on the developments in near-term quantum machine learning seen over the past few years.
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Number of Pages: Xiv, 312 Pages
Language: English
Publication Name: Machine Learning with Quantum Computers
Publisher: Springer International Publishing A&G
Subject: Intelligence (Ai) & Semantics, Probability & Statistics / General
Publication Year: 2022
Type: Textbook
Item Weight: 17.8 Oz
Subject Area: Mathematics, Computers
Author: Francesco Petruccione, Maria Schuld
Item Length: 9.3 in
Series: Quantum Science and Technology Ser.
Item Width: 6.1 in
Format: Trade Paperback
