Isbn: 9798349653261 - the power of quantum machine learning: with tensorflow quantum, qiskit, pennylane, and amazon braket: from algorithms to applications (14 risultati)

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HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Hardback. Condizione: New.

Hardback. Condizione: New.

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Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 292 pp. Englisch.

Hardcover. Condizione: new. Hardcover. Unlock the Future of Intelligence - Where Quantum Computing Meets Machine Learning.The Power of Quantum Machine Learning by Timothy Ugbaja is a groundbreaking exploration of how quantum mechanics and artificial intelligence converge to redefine computation, prediction, optimization, and data-driven decision-making. This book demystifies one of the most revolutionary intersections in modern science-revealing how quantum algorithms can dramatically accelerate learning, pattern recognition, and complex data analysis beyond the limits of classical computing.Designed for data scientists, AI researchers, developers, and forward-thinking engineers, this comprehensive volume bridges the gap between theoretical quantum principles and practical engineering applications. It integrates detailed explanations with hands-on experimentation using today's most advanced frameworks: TensorFlow Quantum, Qiskit, PennyLane, and Amazon Braket.Readers will learn how to design, train, and deploy quantum-enhanced machine learning models using hybrid architectures that unite classical and quantum computing. Each chapter introduces real-world use cases, clear code samples, and cross-platform demonstrations that simplify the complexities of building, optimizing, and scaling quantum models.You'll explore the foundations of quantum data encoding, quantum kernels, variational circuits, and quantum neural networks, gaining the tools to build models that leverage quantum phenomena-superposition, entanglement, and interference-to unlock unprecedented computational potential.Inside this book, you'll learn to: Integrate TensorFlow Quantum with classical ML pipelines for hybrid quantum learning.Apply Qiskit to perform quantum feature encoding, kernel estimation, and classification tasks.Use PennyLane for differentiable quantum programming and deep learning synergy.Run scalable experiments on Amazon Braket's cloud-based quantum hardware.Implement practical examples in optimization, reinforcement learning, and generative models.Beyond algorithms and code, this book also explores the philosophy of quantum intelligence-how learning systems evolve when built on quantum logic instead of classical rules. Through accessible explanations and a systematic, application-driven approach, Timothy Ugbaja empowers readers to harness the next wave of computational evolution.The Power of Quantum Machine Learning is more than a technical reference-it is a visionary guide to the quantum-AI frontier, showing how today's innovators can begin building tomorrow's intelligent systems. Whether you are a Ph.D. student, researcher, data scientist, or technology strategist, this book provides the clarity, structure, and insight needed to lead in the new era of computational intelligence. The Power of Quantum Machine Learning blends theory and practice across TensorFlow Quantum, Qiskit, PennyLane, and Amazon Braket-guiding readers to build scalable AI systems powered by qubits for the next era of intelligence. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …

Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Unlock the Future of Intelligence - Where Quantum Computing Meets Machine Learning.The Power of Quantum Machine Learning by Timothy Ugbaja is a groundbreaking exploration of how quantum mechanics and artificial intelligence converge to redefine computation, prediction, optimization, and data-driven decision-making. This book demystifies one of the most revolutionary intersections in modern science-revealing how quantum algorithms can dramatically accelerate learning, pattern recognition, and complex data analysis beyond the limits of classical computing.Designed for data scientists, AI researchers, developers, and forward-thinking engineers, this comprehensive volume bridges the gap between theoretical quantum principles and practical engineering applications. It integrates detailed explanations with hands-on experimentation using today's most advanced frameworks: TensorFlow Quantum, Qiskit, PennyLane, and Amazon Braket.Readers will learn how to design, train, and deploy quantum-enhanced machine learning models using hybrid architectures that unite classical and quantum computing. Each chapter introduces real-world use cases, clear code samples, and cross-platform demonstrations that simplify the complexities of building, optimizing, and scaling quantum models.You'll explore the foundations of quantum data encoding, quantum kernels, variational circuits, and quantum neural networks, gaining the tools to build models that leverage quantum phenomena-superposition, entanglement, and interference-to unlock unprecedented computational potential.Inside this book, you'll learn to:Integrate TensorFlow Quantum with classical ML pipelines for hybrid quantum learning.Apply Qiskit to perform quantum feature encoding, kernel estimation, and classification tasks.Use PennyLane for differentiable quantum programming and deep learning synergy.Run scalable experiments on Amazon Braket's cloud-based quantum hardware.Implement practical examples in optimization, reinforcement learning, and generative models.Beyond algorithms and code, this book also explores the philosophy of quantum intelligence-how learning systems evolve when built on quantum logic instead of classical rules. Through accessible explanations and a systematic, application-driven approach, Timothy Ugbaja empowers readers to harness the next wave of computational evolution.The Power of Quantum Machine Learning is more than a technical reference-it is a visionary guide to the quantum-AI frontier, showing how today's innovators can begin building tomorrow's intelligent systems. Whether you are a Ph.D. student, researcher, data scientist, or technology strategist, this book provides the clarity, structure, and insight needed to lead in the new era of computational intelligence.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 292 pp. Englisch.…

Buch. Condizione: Neu. The Power of Quantum Machine Learning | WITH TENSORFLOW QUANTUM, QISKIT, PENNYLANE, AND AMAZON BRAKET: FROM ALGORITHMS TO APPLICATIONS | Timothy Ugbaja | Buch | Englisch | 2025 | Tilaverse Inc. | EAN 9798349653261 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …

Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Unlock the Future of Intelligence - Where Quantum Computing Meets Machine Learning.The Power of Quantum Machine Learning by Timothy Ugbaja is a groundbreaking exploration of how quantum mechanics and artificial intelligence converge to redefine computation, prediction, optimization, and data-driven decision-making. This book demystifies one of the most revolutionary intersections in modern science-revealing how quantum algorithms can dramatically accelerate learning, pattern recognition, and complex data analysis beyond the limits of classical computing.Designed for data scientists, AI researchers, developers, and forward-thinking engineers, this comprehensive volume bridges the gap between theoretical quantum principles and practical engineering applications. It integrates detailed explanations with hands-on experimentation using today's most advanced frameworks: TensorFlow Quantum, Qiskit, PennyLane, and Amazon Braket.Readers will learn how to design, train, and deploy quantum-enhanced machine learning models using hybrid architectures that unite classical and quantum computing. Each chapter introduces real-world use cases, clear code samples, and cross-platform demonstrations that simplify the complexities of building, optimizing, and scaling quantum models.You'll explore the foundations of quantum data encoding, quantum kernels, variational circuits, and quantum neural networks, gaining the tools to build models that leverage quantum phenomena-superposition, entanglement, and interference-to unlock unprecedented computational potential.Inside this book, you'll learn to:Integrate TensorFlow Quantum with classical ML pipelines for hybrid quantum learning.Apply Qiskit to perform quantum feature encoding, kernel estimation, and classification tasks.Use PennyLane for differentiable quantum programming and deep learning synergy.Run scalable experiments on Amazon Braket's cloud-based quantum hardware.Implement practical examples in optimization, reinforcement learning, and generative models.Beyond algorithms and code, this book also explores the philosophy of quantum intelligence-how learning systems evolve when built on quantum logic instead of classical rules. Through accessible explanations and a systematic, application-driven approach, Timothy Ugbaja empowers readers to harness the next wave of computational evolution.The Power of Quantum Machine Learning is more than a technical reference-it is a visionary guide to the quantum-AI frontier, showing how today's innovators can begin building tomorrow's intelligent systems. Whether you are a Ph.D. student, researcher, data scientist, or technology strategist, this book provides the clarity, structure, and insight needed to lead in the new era of computational intelligence.…