Description: Please refer to the section BELOW (and NOT ABOVE) this line for the product details - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Title:Machine Learning With Quantum ComputersISBN13:9783030830977ISBN10:3030830977Author:Schuld, Maria (Author), Petruccione, Francesco (Author)Description: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 Binding:Hardcover, HardcoverPublisher:SpringerPublication Date:2021-10-22Weight:0 lbsDimensions:Number of Pages:240Language:English
Price: 144.53 USD
Location: USA
End Time: 2024-11-11T19:54:19.000Z
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Item Length: 9.3in
Item Width: 6.1in
Author: Francesco Petruccione, Maria Schuld
Publication Name: Machine Learning with Quantum Computers
Format: Hardcover
Language: English
Publisher: Springer International Publishing A&G
Publication Year: 2021
Series: Quantum Science and Technology Ser.
Type: Textbook
Item Weight: 23.2 Oz
Number of Pages: Xiv, 312 Pages
