Machine Learning Approach for Cloud Data Analytics in IoT

The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things, focusing on research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. It also highlights cloud-based embedded software development practices to integrate complex machines and increase productivity and reduce operational costs.

Format: Hardback
Length: 528 pages
Publication date: 03 August 2021
Publisher: John Wiley & Sons Inc

The book delves into the multifaceted realm of machine learning, offering a comprehensive perspective through the lens of cloud computing and the Internet of Things (IoT). Spanning from foundational concepts to advanced applications, it explores the diverse dimensions of this rapidly evolving field. Sustainable computing paradigms, such as cloud and fog, possess the remarkable ability to address a wide range of challenges related to performance, storage, processing, maintenance, security, efficiency, integration, cost, energy, and latency. By connecting IoT devices to these environments, decision-making processes related to complex computations and data processing can be expedited, enabling swift and informed actions. Machine learning as a service emerges as a pivotal technology in business intelligence, driving significant investments by organizations seeking to leverage its transformative capabilities.

This comprehensive guide delves into various best practices and their remarkable outcomes in cloud and fog computing environments. It encompasses a wide range of research areas, including big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies showcased in the book are designed to optimize various industry processes, leveraging business intelligence in engineering and technology. Furthermore, the book sheds light on cloud-based embedded software development practices, enabling the integration of complex machines to enhance productivity and reduce operational costs.

Moreover, the book provides a detailed exploration of data science and analytics, which are essential tools for understanding big data and analyzing massive data patterns across diverse sectors. It offers a comprehensive roadmap for practitioners and researchers alike, guiding them in harnessing the power of machine learning and leveraging it to drive innovation and growth in the IoT era.

Weight: 862g
Dimension: 235 x 161 x 32 (mm)
ISBN-13: 9781119785804