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020			_a9789813368156
024	7		_a10.1007/978-981-33-6815-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9.D343 _b2021 EB
245	0	0	_aTrends of Data Science and Applications : _bTheory and Practices _cedited by Siddharth Swarup Rautaray, Phani Pemmaraju, Hrushikesha Mohanty
250			_aFirst edition 2021
264		1	_aSingapore _bSpringer International Publishing _c2021
300			_a1 recurso en línea (XIII, 341 páginas) _b 171 ilustraciones, 140 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aStudies in Computational Intelligence _x1860-9503 _v954
490	0		_aEngineering (SpringerNature-11647)
490	0		_aEngineering (R0) (SpringerNature-43712)
505	0		_aNLP 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. .
520	3		_aThis 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.
988			_aSpringer_Engineering_2021
650		7	_2embne _9162648 _aData mining
650		7	_2embne _9166090 _aAprendizaje automático
650		7	_2embne _aInteligencia artificial _9413115
700	1		_aRautaray, Siddharth Swarup _eeditor literario _0 _1 _4 _4http://id.loc.gov/vocabulary/relators/edt _9681368
700	1		_aPemmaraju, Phani _eeditor literario _4 _4http://id.loc.gov/vocabulary/relators/edt _9681369
700	1		_aMohanty, Hrushikesha _eeditor literario _4 _4http://id.loc.gov/vocabulary/relators/edt _9681370
776	0	8	_iPrinted edition: _z9789813368149
776	0	8	_iPrinted edition: _z9789813368163
776	0	8	_iPrinted edition: _z9789813368170
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-33-6815-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2022 _dz _eIG _zSI