Big-Data Analytics for Cloud, IoT and Cognitive Computing

Nonfiction, Computers, General Computing
Cover of the book Big-Data Analytics for Cloud, IoT and Cognitive Computing by Kai Hwang, Min Chen, Wiley
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Kai Hwang, Min Chen ISBN: 9781119247296
Publisher: Wiley Publication: March 17, 2017
Imprint: Wiley Language: English
Author: Kai Hwang, Min Chen
ISBN: 9781119247296
Publisher: Wiley
Publication: March 17, 2017
Imprint: Wiley
Language: English

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 technologies
  • Covers theory and computing techniques and technologies, making it suitable for use in 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 www.wiley.com/go/hwangIOT

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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.

More books from Wiley

Cover of the book Urban School Leadership by Kai Hwang, Min Chen
Cover of the book After the Internet by Kai Hwang, Min Chen
Cover of the book Red Flag Churches: Distinguishing Protection from Control by Kai Hwang, Min Chen
Cover of the book The International Arms Trade by Kai Hwang, Min Chen
Cover of the book Present Knowledge in Nutrition by Kai Hwang, Min Chen
Cover of the book The Handbook of Global Communication and Media Ethics by Kai Hwang, Min Chen
Cover of the book Monitoring and Modeling the Deepwater Horizon Oil Spill by Kai Hwang, Min Chen
Cover of the book Becoming a Therapist by Kai Hwang, Min Chen
Cover of the book Synthesized Transmission Lines by Kai Hwang, Min Chen
Cover of the book Technische Chemie by Kai Hwang, Min Chen
Cover of the book Computational Design of Lightweight Structures by Kai Hwang, Min Chen
Cover of the book Introduction to Molecular Magnetism by Kai Hwang, Min Chen
Cover of the book Mergers & Acquisitions Integration Handbook by Kai Hwang, Min Chen
Cover of the book Thriving in the New Economy by Kai Hwang, Min Chen
Cover of the book Innovation Capability Maturity Model by Kai Hwang, Min Chen
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy