Quantum Machine Learning

Name: Quantum Machine Learning
Brand: Taylor & Francis Ltd
Price: 367.75 AUD
Availability: PreOrder

Revolutionizing Data Analysis and Optimization

By: Herat Joshi (Editor), Parag Shukla (Editor), Pankaj Tripathi (Editor), Jaiprakash Narain Dwivedi (Editor)

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Hardcover | 1 September 2026 | Edition Number 1

At a Glance

Hardcover
382 Pages

Dimensions(cm)
23.4 x 15.6 x 2.24

Hardcover

$367.75

or 4 interest-free payments of $91.94 with

Available: 1st September 2026

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Quantum computing and machine learning represent two of the most transformative technological advancements of the 21st century. Quantum computing leverages principles such as superposition and entanglement to process information beyond classical limits, while machine learning enables systems to learn patterns and make intelligent decisions from data. The convergence of these fieldsâ"Quantum Machine Learning (QML)â"promises exponential computational advantages, enhanced optimization capabilities, and breakthroughs across finance, healthcare, cybersecurity, telecommunications, and digital transformation.

This book offers a structured and in-depth exploration of Quantum Machine Learning, beginning with foundational quantum principles and progressing to advanced QML algorithms such as Quantum SVMs, quantum kernels, and quantum neural networks. It bridges theory with real-world implementation through domain-focused chapters covering finance, healthcare, taxation systems, mobile networks, supply chains, cybersecurity, augmented reality dashboards, and e-commerce. By integrating conceptual clarity with applied frameworks, the book presents practical pathways for leveraging quantum-enhanced intelligence across industries.

This book is intended for researchers, academicians, postgraduate students, industry professionals, data scientists, technology strategists, and policymakers seeking to understand and apply Quantum Machine Learning in advanced research, enterprise systems, and next-generation digital infrastructures.

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