Machine Learning Approach for Cloud Data Analytics in IoT

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Artificial Intelligence
automatic-update
B01=Jyotir Moy Chatterjee
B01=Monika Mangla
B01=Sachi Nandan Mohanty
B01=Sirisha Potluri
B01=Suneeta Satpathy
Category1=Non-Fiction
Category=UYQ
Challenges and issues in IoT
Challenges in Cloud Data Analytics
Cloud Computing
Cloud Computing and Machine Learning
Cloud computing in Indsutry 4.0
Cloud computing in IoT
COP=United States
Data Analytics
Data analytics in agriculture domain
Data Analytics in Cloud Computing
Data analytics in healthcare Industry
Data analytics in IoT
Data analytics in transport
Data analytics in weather monitoring
Data Analytics using Machine Learning
Data Privacy Issues
Delivery_Delivery within 10-20 working days
Development of Smart cities and Smart home
Energy efficiency in cloud computing. Practical Internet of Things Security
eq_bestseller
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Fog Computing
Internet of Things
IOT enabled Cloud Security
Issues and challenges in Cloud computing
Language_English
Machine Learning
PA=Available
Predictive data analytics
Price_€100 and above
PS=Active
Research issues in Cloud Analytics
softlaunch

Product details

  • ISBN 9781119785804
  • Weight: 454g
  • Dimensions: 10 x 10mm
  • Publication Date: 03 Aug 2021
  • Publisher: John Wiley & Sons Inc
  • Publication City/Country: US
  • Product Form: Hardback
  • Language: English
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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 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.

Audience

Researchers and industry engineers in computer science and artificial intelligence, IT professionals, network administrators, cybersecurity experts.

Sachi Nandan Mohanty received his PhD from IIT Kharagpur 2015 and he is now an associate professor in the Department of Computer Science & Engineering at ICFAI Foundation for Higher Education, Hyderabad, India.

Jyotir Moy Chatterjee is an assistant professor in the IT Department at Lord Buddha Education Foundation (Asia Pacific University of Technology & Innovation), Kathmandu, Nepal.

Monika Mangla received her PhD from Thapar Institute of Engineering & Technology, Patiala, Punjab in 2019, and is now an assistant professor in the Department of Computer Engineering at Lokmanya Tilak College of Engineering (LTCoE), Navi Mumbai, India.

Suneeta Satpathy received her PhD from Utkal University, Bhubaneswar, Odisha in 2015, and is now an associate professor in the Department of Computer Science & Engineering at College of Engineering Bhubaneswar (CoEB), Bhubaneswar, India.

Ms. Sirisha Potluri is an assistant professor in the Department of Computer Science & Engineering at ICFAI Foundation for Higher Education, Hyderabad, India.