Machine Learning with Quantum Computers(Quantum Science and Technology)

使用 量子计算机的机器学习 第2版

理论物理学

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1062.00
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出  版 社
出版时间
2022年10月18日
装      帧
平装
ISBN
9783030831004
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页      码
312
开      本
9.21 x 6.14 x 0.69
语      种
英文
版      次
0002,2021
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图书简介
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. The book 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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