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Trends of data science and applicati...

Mohanty, Hrushikesha.

Trends of data science and applicationstheory and practices /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Trends of data science and applicationsedited by Siddharth Swarup Rautaray, Phani Pemmaraju, Hrushikesha Mohanty.
其他題名:	theory and practices /
其他作者:	Rautaray, Siddharth Swarup.
出版者:	Singapore :Springer Singapore :2021.
面頁冊數:	xiii, 341 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Data mining.
電子資源:	https://doi.org/10.1007/978-981-33-6815-6
ISBN:	9789813368156$q(electronic bk.)

Trends of data science and applicationstheory and practices /
Trends of data science and applicationstheory and practices /[electronic resource] :edited by Siddharth Swarup Rautaray, Phani Pemmaraju, Hrushikesha Mohanty. - Singapore :Springer Singapore :2021. - xiii, 341 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.9541860-949X ;. - Studies in computational intelligence ;v. 216..

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.

ISBN: 9789813368156$q(electronic bk.)

Standard No.: 10.1007/978-981-33-6815-6doiSubjects--Topical Terms:

184440
Data mining.

LC Class. No.: QA76.9.D343 / T746 2021

Dewey Class. No.: 006.312

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