Computing for Data Analysis: Theory and Practices
Chakraborty, Sanjay.
Computing for Data Analysis: Theory and Practices [electronic resource] / by Sanjay Chakraborty, Lopamudra Dey. - 1st ed. 2023. - XVIII, 222 p. 91 illus., 69 illus. in color. online resource. - Data-Intensive Research, 2731-5568 . - Data-Intensive Research, .
Acceso multiusuario
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 .
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.
9789811980046
Computational intelligence.
Quantitative research.
Cloud Computing.
Internet of things.
Computational Intelligence.
Data Analysis and Big Data.
Cloud Computing.
Internet of Things.
Q342
006.3
Computing for Data Analysis: Theory and Practices [electronic resource] / by Sanjay Chakraborty, Lopamudra Dey. - 1st ed. 2023. - XVIII, 222 p. 91 illus., 69 illus. in color. online resource. - Data-Intensive Research, 2731-5568 . - Data-Intensive Research, .
Acceso multiusuario
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 .
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.
9789811980046
Computational intelligence.
Quantitative research.
Cloud Computing.
Internet of things.
Computational Intelligence.
Data Analysis and Big Data.
Cloud Computing.
Internet of Things.
Q342
006.3
