Big-Data Analytics for Cloud, IoT and Cognitive Computing / Kai Hwang, Min Chen.

Format:

Book

Author/Creator:

Hwang, Kai, author.

Chen, Min, 1980- author.

Contributor:

ProQuest ebook central.

Language:

English

Subjects (All):

Cloud computing--Data processing.

Cloud computing.

Big data.

Physical Description:

1 online resource (xvii, 409 pages)

polychrome

Place of Publication:

Chichester, UK ; Hoboken, NJ : John Wiley & Sons Ltd, 2017.

System Details:

text file

Summary:

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 cloud 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 technologies, Covers theory and computing techniques and technologies, making it suitable for use on both computer science and electrical engineering programs, Offers an extremely well-informed vision of future intelligent and cognitive computing environments integrating SMACT technologies, Fully illustrated throughout with examples, figures and approximately 150 problems to support and reinforce learning, Features a companion website with an instructor manual and PowerPoint slides, Big-Data Analytics for Cloud, IoT and Cognitive Computing satisfies the demand among university faculties 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. Book jacket.

Contents:

Big data science and machine intelligence

Smart clouds, virtualization and mashup services

IoT sensing, mobile and cognitive systems

Supervised machine learning algorithms

Unsupervised machine learning and choices of algorithms

Deep learning with artificial neural networks

Programming with hadoop, spark and tensorflow

Machine learning over big data in healthcare applications

Reinforcement deep learning and social media analytics.

Notes:

Includes bibliographical references and index.

Electronic reproduction. Ann Arbor, MI Available via World Wide Web.

Description based on online resource; title from digital title page (viewed on April 28, 2017).

Other Format:

Print version: Hwang, Kai. Big-Data Analytics for Cloud, IoT and Cognitive Computing.

ISBN:

9781119247043

1119247047

Publisher Number:

99976780433

Access Restriction:

Restricted for use by site license.