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Quantum Machine Learning: A Modern Approach by S Karthikeyan: New

US $134.13
ApproximatelyAU $205.59
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eBay item number:405476980889
Last updated on 15 May, 2025 04:19:52 AESTView all revisionsView all revisions

Item specifics

Condition
Brand new: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
Book Title
Quantum Machine Learning: A Modern Approach
Publication Date
2024-10-28
Pages
288
ISBN
9781032544717

About this product

Product Identifiers

Publisher
CRC Press LLC
ISBN-10
1032544716
ISBN-13
9781032544717
eBay Product ID (ePID)
6072309593

Product Key Features

Number of Pages
288 Pages
Publication Name
Quantum Machine Learning : a Modern Approach
Language
English
Subject
Computer Science, General, Computer Engineering
Publication Year
2024
Type
Textbook
Subject Area
Computers, Science
Author
M. Akila
Format
Hardcover

Dimensions

Item Length
9.2 in
Item Width
6.1 in

Additional Product Features

Intended Audience
College Audience
LCCN
2024-014463
Dewey Edition
23/eng/20240617
Illustrated
Yes
Dewey Decimal
006.3/1
Table Of Content
Part I: Introduction to Statistical & Quantum Learning 1: Fundamentals of Statistics 2: Fundamentals of Quantum Machines Part II: Introduction to Quantum Machine Learning 3: Machine Learning with Supervised Quantum Models 4: Machine Learning with Unsupervised Quantum Models 5: Artificial Neural Networks Part III: Quantum Models 6: Quantum Information Science: Bridging the Gap between the Classical and Quantum Worlds 7: Quantum Machine Learning Approaches 8: Quantum Classification 9: Boosting in QMLPart IV: Quantum Evaluation Models 10: Deep Quantum Learning 11: Ensembles and QBoost 12: Quantum Process Tomography and Regression
Synopsis
This book presents the research into and application of machine learning in quantum computation, known as quantum machine learning (QML). It presents a comparison of quantum machine learning, classical machine learning, and traditional programming, along with the usage of quantum computing, toward improving traditional machine learning algorithms through case studies. In summary, the book: Covers the core and fundamental aspects of statistics, quantum learning, and quantum machines. Discusses the basics of machine learning, regression, supervised and unsupervised machine learning algorithms, and artificial neural networks. Elaborates upon quantum machine learning models, quantum machine learning approaches and quantum classification, and boosting. Introduces quantum evaluation models, deep quantum learning, ensembles, and QBoost. Presents case studies to demonstrate the efficiency of quantum mechanics in industrial aspects. This reference text is primarily written for scholars and researchers working in the fields of computer science and engineering, information technology, electrical engineering, and electronics and communication engineering., This text presents the research into and application of machine learning in quantum computation, known as quantum machine learning (QML). It presents a comparison of quantum machine learning, classical machine learning, and traditional programming.
LC Classification Number
Q325.5.Q36 2025

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