Machine Learning with Quantum Computers (2nd ed. 2021) (Quantum Science and Technology)
By: and
Sign Up Now!
Already a Member? Log In
You must be logged into UK education collection to access this title.
Learn about membership options,
or view our freely available titles.
- Synopsis
- 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.
- Copyright:
- 2021
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9783030830984
- Related ISBNs:
- 9783030830977
- Publisher:
- Springer International Publishing
- Date of Addition:
- 11/09/21
- Copyrighted By:
- The Editor
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Science, Computers and Internet, Mathematics and Statistics
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
Reviews
Other Books
- by Maria Schuld
- by Francesco Petruccione
- in Nonfiction
- in Science
- in Computers and Internet
- in Mathematics and Statistics