Computing for Data Analysis: Theory and Practices

This book covers various cutting-edge computing technologies and their applications over data. It discusses in-depth knowledge on big data and cloud computing, quantum computing, cognitive computing, and computational biology with respect to different kinds of data analysis and applications. In this...

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Bibliographic Details
Main Authors: Chakraborty, Sanjay, Dey, Lopamudra (Author)
Format: eBook
Language:English
Published: Singapore Springer Nature Singapore 2023, 2023
Edition:1st ed. 2023
Series:Data-Intensive Research
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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245 0 0 |a Computing for Data Analysis: Theory and Practices  |h Elektronische Ressource  |c by Sanjay Chakraborty, Lopamudra Dey 
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300 |a XVIII, 222 p. 91 illus., 69 illus. in color  |b online resource 
505 0 |a Part 1. Introduction -- Chapter 1. Introduction -- Part 2. Integration of Cloud, Internet of Things, Virtual Reality and Big Data Analytics -- Chapter 2. Impact of Big Data and Cloud Computing on Data Analysis -- Chapter 3. Edge Computing with Internet of Things (IoT) and Data Analysis -- Chapter 4. Virtual and Augmented Reality with Embedded Systems -- Part 3. Biological Applications of Data Analytics -- Chapter 5. Computational Biology towards Data Analysis -- Chapter 6. Data Classification through Cognitive Computing -- Part 4. Quantum Computing for Data Analysis -- Chapter 7. Quantum Computing in Machine Learning -- Chapter 8. Quantum Computing in Image Processing -- Part 5. Computations for Various Data Applications and Future -- Chapter 9. Challenges and Future Research Directions on Data Computation 
653 |a Data Analysis and Big Data 
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653 |a Computational intelligence 
653 |a Quantitative research 
653 |a Computational Intelligence 
653 |a Cloud Computing 
653 |a Internet of Things 
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520 |a This book covers various cutting-edge computing technologies and their applications over data. It discusses in-depth knowledge on big data and cloud computing, quantum computing, cognitive computing, and computational biology with respect to different kinds of data analysis and applications. In this book, authors describe some interesting models in the cloud, quantum, cognitive, and computational biology domains that provide some useful impact on intelligent data (emotional, image, etc.) analysis. They also explain how these computing technologies based data analysis approaches used for various real-life applications. The book will be beneficial for readers working in this area