Quantum Machine Learning With Python (Record no. 67128)

MARC details
000 -LEADER
fixed length control field 02523nam a22002297a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260306110207.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781484284520
028 ## - DISTRIBUTOR NAME
Distributor Name : Savera Book Distributors
Distributor address : 4754 Akarshan Bhawaqn, 23 Ansari Road, Darya Ganj, New Delhi
Bill Number : 25-26/CRB/1090
Bill Date : 02/03/2026
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31 PAT
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Pattanayak, Santanu.
245 ## - TITLE STATEMENT
Title Quantum Machine Learning With Python
Remainder of title : Using Cirq from Google Research and IBM Qiskit .
Statement of responsibility, etc /Santanu Pattanayak.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc , Bangalore
Name of publisher, distributor, etc : Apress
Date of publication, distribution, etc , 2021.
300 ## - PHYSICAL DESCRIPTION
Extent xix, 361p.
Dimensions : 26cm.
365 ## - TRADE PRICE
Price amount 26cm.
520 ## - SUMMARY, ETC.
Summary, etc Quickly scale up to Quantum computing and Quantum machine learning foundations and related mathematics and expose them to different use cases that can be solved through Quantum based algorithms. This book explains Quantum Computing, which leverages the Quantum mechanical properties sub-atomic particles. It also examines Quantum machine learning, which can help solve some of the most challenging problems in forecasting, financial modeling, genomics, cybersecurity, supply chain logistics, cryptography among others. You'll start by reviewing the fundamental concepts of Quantum Computing, such as Dirac Notations, Qubits, and Bell state, followed by postulates and mathematical foundations of Quantum Computing. Once the foundation base is set, you'll delve deep into Quantum based algorithms including Quantum Fourier transform, phase estimation, and HHL (Harrow-Hassidim-Lloyd) among others. You'll then be introduced to Quantum machine learning and Quantum deep learning-based algorithms, along with advanced topics of Quantum adiabatic processes and Quantum based optimization. Throughout the book, there are Python implementations of different Quantum machine learning and Quantum computing algorithms using the Qiskit toolkit from IBM and Cirq from Google Research. What You'll LearnUnderstand Quantum computing and Quantum machine learningExplore varied domains and the scenarios where Quantum machine learning solutions can be appliedDevelop expertise in algorithm development in varied Quantum computing frameworksReview the major challenges of building large scale Quantum computers and applying its various techniquesWho This Book Is ForMachine Learning enthusiasts and engineers who want to quickly scale up to Quantum Machine Learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Python
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine Learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Quantum Machine Learning
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Santanu Pattanayak.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Total Renewals Full call number Barcode Date last seen Date checked out Price effective from Koha item type
    Dewey Decimal Classification     SNU LIBRARY SNU LIBRARY 06/03/2026 Savera Book Distributors 1049.00 2 2 006.31 PAT 31379 12/10/2026 09/04/2026 06/03/2026 Books
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