Big Data for IoT, Cloud, and AI offers a detailed exploration of big data, focusing on its integration with IoT, cloud computing, and AI technologies. This book is divided into seven chapters, presented in a logical sequence across two main parts.
The first part covers three chapters on data science, the role of clouds, and IoT in big data computing. We delve into technologies that explore smart cloud computing, big data analytics, and cognitive machine learning capabilities. Topics include cloud architecture, IoT, cognitive systems, and mobile cloud interaction frameworks.
The second part comprises four chapters focusing on machine learning principles, data analytics, and deep learning in big data applications. We discuss supervised and unsupervised machine learning methods and deep learning with artificial neural networks. Brain-inspired computer architectures like IBM's SyNapse TrueNorth processors, Google's tensor processing unit, and China's Cambricon chips are also covered. Additionally, big data analytics in healthcare is explored.
This book aims to integrate big data theories with cloud design principles and supercomputing standards, promoting big data computing on smart clouds and distributed datacenters. We provide insights for leveraging computer, analytical, and application skills to advance career development, business transformation, and scientific discovery in the world of big data.
