harnessing inference intelligent decision making (14 resultados)

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condición: New.

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

Paperback. Condición: New.

Paperback. Condición: new. Paperback. In a world where data never stops moving, the ability to act on information in real time has become a defining advantage. Financial systems must detect fraud the instant it happens, healthcare platforms must monitor patients continuously, and supply chains must adapt to disruptions as they unfold. Success no longer depends only on collecting data, it depends on transforming it into actionable intelligence in milliseconds. Artificial intelligence (AI) bridges this gap. By embedding AI inference into real-time data pipelines, organizations can move from reacting to events to anticipating them, making decisions that are faster, smarter, and more reliable. Harnessing AI Inference for Intelligent Decision-Making in Real-Time Dataflows examines how AI inference can be seamlessly embedded into real-time dataflows to enable faster, smarter, and more responsible decision-making. This book bridges theoretical advancements, emerging technologies, and real-world use cases, providing a roadmap for designing and managing AI-driven systems that operate at the edge of speed, scale, and responsibility. Covering topics such as smart cities, federated learning, and the internet of things (IoT), this book is an excellent resource for graduate and doctoral students, researchers, engineers, developers, system architects, business leaders, policymakers, and more. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condición: new. Paperback. In a world where data never stops moving, the ability to act on information in real time has become a defining advantage. Financial systems must detect fraud the instant it happens, healthcare platforms must monitor patients continuously, and supply chains must adapt to disruptions as they unfold. Success no longer depends only on collecting data, it depends on transforming it into actionable intelligence in milliseconds. Artificial intelligence (AI) bridges this gap. By embedding AI inference into real-time data pipelines, organizations can move from reacting to events to anticipating them, making decisions that are faster, smarter, and more reliable. Harnessing AI Inference for Intelligent Decision-Making in Real-Time Dataflows examines how AI inference can be seamlessly embedded into real-time dataflows to enable faster, smarter, and more responsible decision-making. This book bridges theoretical advancements, emerging technologies, and real-world use cases, providing a roadmap for designing and managing AI-driven systems that operate at the edge of speed, scale, and responsibility. Covering topics such as smart cities, federated learning, and the internet of things (IoT), this book is an excellent resource for graduate and doctoral students, researchers, engineers, developers, system architects, business leaders, policymakers, and more. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Hardcover. Condición: new. Hardcover. In a world where data never stops moving, the ability to act on information in real time has become a defining advantage. Financial systems must detect fraud the instant it happens, healthcare platforms must monitor patients continuously, and supply chains must adapt to disruptions as they unfold. Success no longer depends only on collecting data, it depends on transforming it into actionable intelligence in milliseconds. Artificial intelligence (AI) bridges this gap. By embedding AI inference into real-time data pipelines, organizations can move from reacting to events to anticipating them, making decisions that are faster, smarter, and more reliable. Harnessing AI Inference for Intelligent Decision-Making in Real-Time Dataflows examines how AI inference can be seamlessly embedded into real-time dataflows to enable faster, smarter, and more responsible decision-making. This book bridges theoretical advancements, emerging technologies, and real-world use cases, providing a roadmap for designing and managing AI-driven systems that operate at the edge of speed, scale, and responsibility. Covering topics such as smart cities, federated learning, and the internet of things (IoT), this book is an excellent resource for graduate and doctoral students, researchers, engineers, developers, system architects, business leaders, policymakers, and more. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Condición: new. Hardcover. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condición: new. Paperback. In a world where data never stops moving, the ability to act on information in real time has become a defining advantage. Financial systems must detect fraud the instant it happens, healthcare platforms must monitor patients continuously, and supply chains must adapt to disruptions as they unfold. Success no longer depends only on collecting data, it depends on transforming it into actionable intelligence in milliseconds. Artificial intelligence (AI) bridges this gap. By embedding AI inference into real-time data pipelines, organizations can move from reacting to events to anticipating them, making decisions that are faster, smarter, and more reliable. Harnessing AI Inference for Intelligent Decision-Making in Real-Time Dataflows examines how AI inference can be seamlessly embedded into real-time dataflows to enable faster, smarter, and more responsible decision-making. This book bridges theoretical advancements, emerging technologies, and real-world use cases, providing a roadmap for designing and managing AI-driven systems that operate at the edge of speed, scale, and responsibility. Covering topics such as smart cities, federated learning, and the internet of things (IoT), this book is an excellent resource for graduate and doctoral students, researchers, engineers, developers, system architects, business leaders, policymakers, and more. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Condición: Neu. Harnessing AI Inference for Intelligent Decision-Making in Real-Time Dataflows | Abu Sarwar Zamani (u. a.) | Taschenbuch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798337370477 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Hardcover. Condición: new. Hardcover. In a world where data never stops moving, the ability to act on information in real time has become a defining advantage. Financial systems must detect fraud the instant it happens, healthcare platforms must monitor patients continuously, and supply chains must adapt to disruptions as they unfold. Success no longer depends only on collecting data, it depends on transforming it into actionable intelligence in milliseconds. Artificial intelligence (AI) bridges this gap. By embedding AI inference into real-time data pipelines, organizations can move from reacting to events to anticipating them, making decisions that are faster, smarter, and more reliable. Harnessing AI Inference for Intelligent Decision-Making in Real-Time Dataflows examines how AI inference can be seamlessly embedded into real-time dataflows to enable faster, smarter, and more responsible decision-making. This book bridges theoretical advancements, emerging technologies, and real-world use cases, providing a roadmap for designing and managing AI-driven systems that operate at the edge of speed, scale, and responsibility. Covering topics such as smart cities, federated learning, and the internet of things (IoT), this book is an excellent resource for graduate and doctoral students, researchers, engineers, developers, system architects, business leaders, policymakers, and more. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Buch. Condición: Neu. Harnessing AI Inference for Intelligent Decision-Making in Real-Time Dataflows | Abu Sarwar Zamani (u. a.) | Buch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798337370460 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In a world where data never stops moving, the ability to act on information in real time has become a defining advantage. Financial systems must detect fraud the instant it happens, healthcare platforms must monitor patients continuously, and supply chains must adapt to disruptions as they unfold. Success no longer depends only on collecting data, it depends on transforming it into actionable intelligence in milliseconds. Artificial intelligence (AI) bridges this gap. By embedding AI inference into real-time data pipelines, organizations can move from reacting to events to anticipating them, making decisions that are faster, smarter, and more reliable. Harnessing AI Inference for Intelligent Decision-Making in Real-Time Dataflows examines how AI inference can be seamlessly embedded into real-time dataflows to enable faster, smarter, and more responsible decision-making. This book bridges theoretical advancements, emerging technologies, and real-world use cases, providing a roadmap for designing and managing AI-driven systems that operate at the edge of speed, scale, and responsibility. Covering topics such as smart cities, federated learning, and the internet of things (IoT), this book is an excellent resource for graduate and doctoral students, researchers, engineers, developers, system architects, business leaders, policymakers, and more.

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In a world where data never stops moving, the ability to act on information in real time has become a defining advantage. Financial systems must detect fraud the instant it happens, healthcare platforms must monitor patients continuously, and supply chains must adapt to disruptions as they unfold. Success no longer depends only on collecting data, it depends on transforming it into actionable intelligence in milliseconds. Artificial intelligence (AI) bridges this gap. By embedding AI inference into real-time data pipelines, organizations can move from reacting to events to anticipating them, making decisions that are faster, smarter, and more reliable. Harnessing AI Inference for Intelligent Decision-Making in Real-Time Dataflows examines how AI inference can be seamlessly embedded into real-time dataflows to enable faster, smarter, and more responsible decision-making. This book bridges theoretical advancements, emerging technologies, and real-world use cases, providing a roadmap for designing and managing AI-driven systems that operate at the edge of speed, scale, and responsibility. Covering topics such as smart cities, federated learning, and the internet of things (IoT), this book is an excellent resource for graduate and doctoral students, researchers, engineers, developers, system architects, business leaders, policymakers, and more.