ARTIFICIAL INTELLIGENCE FOR QUANTUM MACHINE LEARNING: Algorithms, Applications, and Future Trends in Quantum AI - Brossura
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Artificial Intelligence for Quantum Machine Learning
In the ever-evolving landscape of technology, Artificial Intelligence (AI) and Quantum Computing stand at the forefront of innovation. Artificial Intelligence for Quantum Machine Learning is a comprehensive guide that explores the powerful synergy between these two cutting-edge fields, unlocking new possibilities for data processing, pattern recognition, and complex problem-solving.
This book delves into the fundamental concepts of AI and quantum computing, providing a strong foundation in qubits, superposition, entanglement, and quantum circuits. It explains how Quantum Machine Learning (QML) algorithms, including Quantum Neural Networks (QNNs), Quantum Support Vector Machines (QSVMs), and Variational Quantum Circuits (VQCs), offer revolutionary improvements over classical machine learning approaches.
With a focus on practical applications, real-world challenges, and future developments, this book covers:
The key differences between classical and quantum machine learning
How quantum algorithms optimize AI performance
Hands-on insights into frameworks like IBM Qiskit, Google Cirq, and Microsoft Q#
The role of hybrid quantum-classical AI models in today’s technological landscape
The biggest challenges in scalability, quantum error correction, and hardware limitations
Whether you are a data scientist, AI researcher, quantum computing enthusiast, or tech visionary, Artificial Intelligence for Quantum Machine Learning equips you with the knowledge to navigate the next frontier of intelligent computing. As Quantum AI continues to evolve, this book provides the insights needed to stay ahead of the curve and embrace the quantum-powered future of machine learning.
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Artificial Intelligence for Quantum Machine Learning (Paperback)
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Paperback. Condizione: new. Paperback. Artificial Intelligence for Quantum Machine LearningIn the ever-evolving landscape of technology, Artificial Intelligence (AI) and Quantum Computing stand at the forefront of innovation. Artificial Intelligence for Quantum Machine Learning is a comprehensive guide that explores the powerful synergy between these two cutting-edge fields, unlocking new possibilities for data processing, pattern recognition, and complex problem-solving.This book delves into the fundamental concepts of AI and quantum computing, providing a strong foundation in qubits, superposition, entanglement, and quantum circuits. It explains how Quantum Machine Learning (QML) algorithms, including Quantum Neural Networks (QNNs), Quantum Support Vector Machines (QSVMs), and Variational Quantum Circuits (VQCs), offer revolutionary improvements over classical machine learning approaches.With a focus on practical applications, real-world challenges, and future developments, this book covers: The key differences between classical and quantum machine learningHow quantum algorithms optimize AI performanceHands-on insights into frameworks like IBM Qiskit, Google Cirq, and Microsoft Q#The role of hybrid quantum-classical AI models in today's technological landscapeThe biggest challenges in scalability, quantum error correction, and hardware limitationsWhether you are a data scientist, AI researcher, quantum computing enthusiast, or tech visionary, Artificial Intelligence for Quantum Machine Learning equips you with the knowledge to navigate the next frontier of intelligent computing. As Quantum AI continues to evolve, this book provides the insights needed to stay ahead of the curve and embrace the quantum-powered future of machine learning. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9798310546240
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ARTIFICIAL INTELLIGENCE FOR QUANTUM MACHINE LEARNING: Algorithms, Applications, and Future Trends in Quantum AI
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Artificial Intelligence for Quantum Machine Learning (Paperback)
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Paperback. Condizione: new. Paperback. Artificial Intelligence for Quantum Machine LearningIn the ever-evolving landscape of technology, Artificial Intelligence (AI) and Quantum Computing stand at the forefront of innovation. Artificial Intelligence for Quantum Machine Learning is a comprehensive guide that explores the powerful synergy between these two cutting-edge fields, unlocking new possibilities for data processing, pattern recognition, and complex problem-solving.This book delves into the fundamental concepts of AI and quantum computing, providing a strong foundation in qubits, superposition, entanglement, and quantum circuits. It explains how Quantum Machine Learning (QML) algorithms, including Quantum Neural Networks (QNNs), Quantum Support Vector Machines (QSVMs), and Variational Quantum Circuits (VQCs), offer revolutionary improvements over classical machine learning approaches.With a focus on practical applications, real-world challenges, and future developments, this book covers: The key differences between classical and quantum machine learningHow quantum algorithms optimize AI performanceHands-on insights into frameworks like IBM Qiskit, Google Cirq, and Microsoft Q#The role of hybrid quantum-classical AI models in today's technological landscapeThe biggest challenges in scalability, quantum error correction, and hardware limitationsWhether you are a data scientist, AI researcher, quantum computing enthusiast, or tech visionary, Artificial Intelligence for Quantum Machine Learning equips you with the knowledge to navigate the next frontier of intelligent computing. As Quantum AI continues to evolve, this book provides the insights needed to stay ahead of the curve and embrace the quantum-powered future of machine learning. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9798310546240
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