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Quantum Machine Learning (QML): Reality in 2025

by Ethan Kimura
Sold out
Current price ₹1,247.00
Original price ₹1,328.00
Original price ₹1,328.00
Original price ₹1,328.00
(-6%)
₹1,247.00
Current price ₹1,247.00

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Book cover type: Paperback
  • ISBN13: 9798314974933
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Publication Date:
  • Pages: 230
  • Original Price: GBP 11.54
  • Language: English
  • Edition: N/A
  • Item Weight: 313 grams
  • BISAC Subject(s): Physics / Quantum Theory

Quantum Machine Learning (QML): Reality in 2025 is a deep dive into the intersection of quantum computing and artificial intelligence, exploring how quantum technology is poised to revolutionize machine learning.

As advancements in quantum hardware accelerate, researchers and industry leaders are working toward harnessing quantum mechanics-superposition, entanglement, and interference-to solve complex problems that classical systems struggle with. This book provides a clear and accessible overview of quantum machine learning, detailing the fundamental principles of quantum computing and its implications for AI model training, optimization, and data processing.

From the foundational concepts of qubits and quantum circuits to cutting-edge quantum algorithms for supervised and unsupervised learning, the book guides readers through the latest breakthroughs and challenges in the field. It examines hybrid quantum-classical approaches, real-world applications in industries such as finance, healthcare, and cybersecurity, and the ethical considerations surrounding this emerging technology.

Quantum Machine Learning (QML): Reality in 2025 is an essential read for AI researchers, data scientists, technology enthusiasts, and anyone interested in the future of artificial intelligence and quantum computing. Whether you're a professional looking to stay ahead in a rapidly evolving field or a curious reader eager to understand the next frontier of technology, this book provides the insights needed to grasp the transformative potential of QML.

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