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Trends of Data Science and Applications [electronic resource] : Theory and Practices / edited by Siddharth Swarup Rautaray, Phani Pemmaraju, Hrushikesha Mohanty.

Contributor(s): Rautaray, Siddharth Swarup [editor.] | Pemmaraju, Phani [editor.] | Mohanty, Hrushikesha [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Computational Intelligence: 954 Publisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2021Edition: 1st ed. 2021.Description: XIII, 341 p. 171 illus., 140 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9789813368156.Subject(s): Data structures (Computer science) | Information theory | Database management | Data mining | Artificial intelligence | Data Structures and Information Theory | Database Management | Data Mining and Knowledge Discovery | Artificial IntelligenceAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 005.73 | 003.54 Online resources: Click here to access online
Contents:
NLP for Sentiment Computation -- Productizing an Artificial Intelligence solution for Intelligent Detail Extraction- Synergy of Symbolic and Sub-symbolic Artificial Intelligence techniques -- Digital Consumption Pattern and Impacts of Social Media: Descriptive Statistical Analysis -- Applicational Statistics in Data Science & Machine Learning -- Evolutionary algorithms based machine learning models -- Application to Predict the Impact of COVID-19 in India using Deep Learning -- Role of Data Analytics in Bio Cyber Physical Systems -- Evolution of Sentiment Analysis : Methodologies and Paradigms -- Healthcare Analytics: An advent to mitigate the risks and impacts of a Pandemic -- Image Classification for Binary Classes using Deep Convolutional Neural Network: An Experimental Study. .
In: Springer Nature eBookSummary: This book includes an extended version of selected papers presented at the 11th Industry Symposium 2021 held during January 7–10, 2021. The book covers contributions ranging from theoretical and foundation research, platforms, methods, applications, and tools in all areas. It provides theory and practices in the area of data science, which add a social, geographical, and temporal dimension to data science research. It also includes application-oriented papers that prepare and use data in discovery research. This book contains chapters from academia as well as practitioners on big data technologies, artificial intelligence, machine learning, deep learning, data representation and visualization, business analytics, healthcare analytics, bioinformatics, etc. This book is helpful for the students, practitioners, researchers as well as industry professional.
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NLP for Sentiment Computation -- Productizing an Artificial Intelligence solution for Intelligent Detail Extraction- Synergy of Symbolic and Sub-symbolic Artificial Intelligence techniques -- Digital Consumption Pattern and Impacts of Social Media: Descriptive Statistical Analysis -- Applicational Statistics in Data Science & Machine Learning -- Evolutionary algorithms based machine learning models -- Application to Predict the Impact of COVID-19 in India using Deep Learning -- Role of Data Analytics in Bio Cyber Physical Systems -- Evolution of Sentiment Analysis : Methodologies and Paradigms -- Healthcare Analytics: An advent to mitigate the risks and impacts of a Pandemic -- Image Classification for Binary Classes using Deep Convolutional Neural Network: An Experimental Study. .

This book includes an extended version of selected papers presented at the 11th Industry Symposium 2021 held during January 7–10, 2021. The book covers contributions ranging from theoretical and foundation research, platforms, methods, applications, and tools in all areas. It provides theory and practices in the area of data science, which add a social, geographical, and temporal dimension to data science research. It also includes application-oriented papers that prepare and use data in discovery research. This book contains chapters from academia as well as practitioners on big data technologies, artificial intelligence, machine learning, deep learning, data representation and visualization, business analytics, healthcare analytics, bioinformatics, etc. This book is helpful for the students, practitioners, researchers as well as industry professional.

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