big data analytics cloud iot (57 resultados)

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hardcover. Condición: Gut. 500 Seiten; 9781119904885.3 Gewicht in Gramm: 1.

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Hardcover. Condición: new. Hardcover. The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. To that end, the authors draw upon their original research and proven track record in the field to describe a practical approach integrating big-data theories, cloud design principles, Internet of Things (IoT) sensing, machine learning, data analytics and Hadoop and Spark programming. Part 1 focuses on data science, the roles of clouds and IoT devices and frameworks for big-data computing. Big data analytics and cognitive machine learning, as well as cloud architecture, IoT and cognitive systems are explored, and mobile cloud-IoT-interaction frameworks are illustrated with concrete system design examples. Part 2 is devoted to the principles of and algorithms for machine learning, data analytics and deep learning in big data applications. Part 3 concentrates on cloud programming software libraries from MapReduce to Hadoop, Spark and TensorFlow and describes business, educational, healthcare and social media applications for those tools. The first book describing a practical approach to integrating social, mobile, analytics, cloud and IoT (SMACT) principles and technologiesCovers theory and computing techniques and technologies, making it suitable for use in both computer science and electrical engineering programsOffers an extremely well-informed vision of future intelligent and cognitive computing environments integrating SMACT technologiesFully illustrated throughout with examples, figures and approximately 150 problems to support and reinforce learningFeatures a companion website with an instructor manual and PowerPoint slides Big-Data Analytics for Cloud, IoT and Cognitive Computing satisfies the demand among university faculty and students for cutting-edge information on emerging intelligent and cognitive computing systems and technologies. Professionals working in data science, cloud computing and IoT applications will also find this book to be an extremely useful working resource. The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makersserves as an excellent resource for establishing the relationship of machine learning with IoT, big data, and cognitive and cloud computing to give you an overview of how these modern areas of computing relate to each other.This book introduces a collection of the most important concepts of machine learning and sets them in context with other vital technologies that decision makers need to know about. These concepts span the process from envisioning the problem to applying machine-learning techniques to your particular situation. This discussion also provides an insight to help deploy the results to improve decision-making.The book uses case studies and jargon busting to help you grasp the theory of machine learning quickly. You'll soon gain the big picture of machine learning and how it fits with other cutting-edge IT services. This knowledge will give you confidence in your decisions for the future of your business.What You Will LearnDiscover the machine learning, big data, and cloud and cognitive computing technology stackGain insights into machine learning concepts and practicesUnderstand business and enterprise decision-making using machine learningAbsorb machine-learning best practicesWho This Book Is ForManagers tasked with making key decisions who want to learn how and when machine learning and related technologies can help them.

Taschenbuch. Condición: Neu. Machine Learning for Decision Makers | Cognitive Computing Fundamentals for Better Decision Making. In the Age of IoT, Big Data Analytics, the Cloud, and Cognitive Computing | Patanjali Kashyap | Taschenbuch | Englisch | Apress | EAN 9781484229873 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

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Hardback. Condición: New. New copy - Usually dispatched within 4 working days. 929.

Condición: New. The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. Num Pages: 432 pages. BIC Classification: TJ; UT. Category: (P) Professional & Vocational. Dimension: 244 x 170. . . 2017. 1st Edition. Hardcover. . . . .

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Hardback. Condición: New. As enterprise access networks evolve with a larger number of mobile users, a wide range of devices and new cloud-based applications, managing user performance on an end-to-end basis has become rather challenging. Recent advances in big data network analytics combined with AI and cloud computing are being leveraged to tackle this growing problem. AI is becoming further integrated with software that manage networks, storage, and can compute. This edited book focuses on how new network analytics, IoTs and Cloud Computing platforms are being used to ingest, analyse and correlate a myriad of big data across the entire network stack in order to increase quality of service and quality of experience (QoS/QoE) and to improve network performance. From big data and AI analytical techniques for handling the huge amount of data generated by IoT devices, the authors cover cloud storage optimization, the design of next generation access protocols and internet architecture, fault tolerance and reliability in intelligent networks, and discuss a range of emerging applications. This book will be useful to researchers, scientists, engineers, professionals, advanced students and faculty members in ICTs, data science, networking, AI, machine learning and sensing. It will also be of interest to professionals in data science, AI, cloud and IoT start-up companies, as well as developers and designers.

Hardcover. Condición: new. Hardcover. The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. To that end, the authors draw upon their original research and proven track record in the field to describe a practical approach integrating big-data theories, cloud design principles, Internet of Things (IoT) sensing, machine learning, data analytics and Hadoop and Spark programming. Part 1 focuses on data science, the roles of clouds and IoT devices and frameworks for big-data computing. Big data analytics and cognitive machine learning, as well as cloud architecture, IoT and cognitive systems are explored, and mobile cloud-IoT-interaction frameworks are illustrated with concrete system design examples. Part 2 is devoted to the principles of and algorithms for machine learning, data analytics and deep learning in big data applications. Part 3 concentrates on cloud programming software libraries from MapReduce to Hadoop, Spark and TensorFlow and describes business, educational, healthcare and social media applications for those tools. The first book describing a practical approach to integrating social, mobile, analytics, cloud and IoT (SMACT) principles and technologiesCovers theory and computing techniques and technologies, making it suitable for use in both computer science and electrical engineering programsOffers an extremely well-informed vision of future intelligent and cognitive computing environments integrating SMACT technologiesFully illustrated throughout with examples, figures and approximately 150 problems to support and reinforce learningFeatures a companion website with an instructor manual and PowerPoint slides Big-Data Analytics for Cloud, IoT and Cognitive Computing satisfies the demand among university faculty and students for cutting-edge information on emerging intelligent and cognitive computing systems and technologies. Professionals working in data science, cloud computing and IoT applications will also find this book to be an extremely useful working resource. The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Gebunden. Condición: New. Kai Hwang, PhD is Professor of Electrical Engineering and Computer Science at University of Southern California, USA. He also serves as an EMC-endowed visiting Chair Professor at Tsinghua University, China. He specializes in computer architecture, wireless .

Condición: New. The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. Num Pages: 432 pages. BIC Classification: TJ; UT. Category: (P) Professional & Vocational. Dimension: 244 x 170. . . 2017. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.

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Hardcover. Condición: Brand New. 350 pages. 9.21x6.14x1.00 inches. In Stock.