Machine Learning Approach for Cloud Data Analytics in IoT
- 7h 50m
- Jyotir Moy Chatterjee, Monika Mangla, Sachi Nandan Mohanty, Sirisha Potluri, Suneeta Satpathy
- John Wiley & Sons (US)
- 2021
The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications
Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology.
Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various 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. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.
In this Book
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Machine Learning–Based Data Analysis
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Machine Learning for Cyber-Immune IoT Applications
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Employing Machine Learning Approaches for Predictive Data Analytics in Retail Industry
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Emerging Cloud Computing Trends for Business Transformation
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Security of Sensitive Data in Cloud Computing
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Cloud Cryptography for Cloud Data Analytics in IoT
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Issues and Challenges of Classical Cryptography in Cloud Computing
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Cloud-Based Data Analytics for Monitoring Smart Environments
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Performance Metrics for Comparison of Heuristics Task Scheduling Algorithms in Cloud Computing Platform
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Smart Environment Monitoring Models Using Cloud-Based Data Analytics: A Comprehensive Study
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Advancement of Machine Learning and Cloud Computing in the Field of Smart Health Care
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Study on Green Cloud Computing—A Review
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Intelligent Reclamation of Plantae Affliction Disease
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Prediction of the Stock Market Using Machine Learning–Based Data Analytics
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Pehchaan: Analysis of the 'Aadhar Dataset' to Facilitate a Smooth and Efficient Conduct of the Upcoming NPR
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Deep Learning Approach for Resource Optimization in Blockchain, Cellular Networks, and IoT: Open Challenges and Current Solutions
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Unsupervised Learning in Accordance With New Aspects of Artificial Intelligence
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Predictive Modeling of Anthropomorphic Gamifying Blockchain-Enabled Transitional Healthcare System
