Big Data for Cloud, Iot And Cognitive Computing

This book consists of seven chapters, in a logical flow, divided into two parts. The first part consists of three chapters on data science, the role of clouds, and IoT in big data computing. In these three chapters, we have covered technologies to explore smart cloud computing with big data analytics and cognitive machine learning abilities. In addition, we have covered cloud architecture, IoT, and cognitive systems. Finally, we have also presented mobile clouds and IoT interaction frameworks.

The second part has four chapters covering principles and algorithms for machine learning, data analytics, and deep learning in big data applications. We have covered supervised as well as unsupervised machine learning methods and deep learning with artificial neural networks. We have presented brain-inspired computer architectures, for instance, SyNapse TrueNorth processors of IBM, Google’s tensor processing unit used in Brain programs, and Cambricon chips of China. These four chapters are the basic foundation for design methodologies and algorithm implementations. We have also presented big data analytics for machine learning for healthcare.

We have taken a technological fusion approach by integrating big data theories with cloud design principles and supercomputing standards to promote big data computing on smart clouds or supercomputers. We aim to benefit those who wish to leverage their computer, analytical, and application skills to push for career development, business transformation, and scientific discovery in the world of big data. This book integrates big data theories with evolving technologies on smart clouds and explores distributed data centers with new applications.
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