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010 a| 2021016674;

020 a| 9781000454543q| (epub);

020 a| 9781003038450q| (ebk);

020 z| 9780367466633q| (hbk);

020 z| 9781032104461q| (pbk);

035 a| (WaSeSS)ssj0002468174;

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050 00 a| Q325.5;

082 00 a| 006.3/12| 23;

245 00 a| Integrating deep learning algorithms to overcome challenges in big data analyticsh| [electronic resource] /c| edited by R. Sujatha, S.L. Aarthy, and R. Vettriselvan.;

260 a| Boca Raton ;a| Abingdon, Oxon :b| CRC Press,c| 2022.;

300 a| 1 online resource;

490 0 a| Green engineering and technology: concepts and applications;

504 a| Includes bibliographical references and index.;

506 a| Available only to authorized users.;

520 a| "Data science revolves around two giants, which are big data analytics and deep learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of big data along with deep learning systems. This book discusses how big data along with deep learning holds the potential to significantly increase data understanding and decision making. It also covers numerous applications in healthcare, education, communications, media, and the entertainment industry. The book offers innovative platforms for integrating big data and deep learning and presents issues related to adequate data store, sematic indexing, data tagging, and fast information retrieval. The audience includes industry professionals, academic professors, research scholars, system modelling, and simulation experts"--c| Provided by publisher.;

538 a| Mode of access: World Wide Web;

588 a| Description based on print version record and CIP data provided by publisher.;

650 0 a| Machine learningx| Industrial applications.=| ^A145211;

650 0 a| Big data.=| ^A1157100;

650 0 a| Artificial intelligencex| Industrial applications.=| ^A15394;

650 0 a| Algorithms.=| ^A17554;

655 0 a| Electronic books.=| ^A491897;

700 1 a| Sujatha, R.c| (Computer science professor)?| UNAUTHORIZED;

700 1 a| Aarthy, S. L.?| UNAUTHORIZED;

700 1 a| Vettriselvan, R.?| UNAUTHORIZED;

776 08 i| Print version:t| Integrating deep learning algorithms to overcome challenges in big data analyticsd| Boca Raton : CRC Press, 2022z| 9780367466633w| (DLC) 2021016673;

856 40 z| Full text available from Taylor & Francis eBooksu| https://go.openathens.net/redirector/ecu.edu?url=https%3A%2F%2Fwww.taylorfrancis.com%2Fbooks%2F9781003038450;

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999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 6672258-1001l| JNETm| JOYNERr| Ys| Yt| JNESSBKu| 12/19/2025x| EBOOKz| JERESOURCE;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 6672258-2001l| HSLELECm| HSLr| Ys| Yt| HEBKu| 12/19/2025x| EBOOKz| HERESOURCE;

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Integrating deep learning algorithms to overcome challenges in big data analytics / edited by R. Sujatha, S.L. Aarthy, and R. Vettriselvan.

Other author	Sujatha, R. (Computer science professor)
Other author	Aarthy, S. L.
Other author	Vettriselvan, R.
Format	Electronic
Publication Info	Boca Raton ; Abingdon, Oxon : CRC Press, 2022.
Description	1 online resource
Supplemental Content	Full text available from Taylor & Francis eBooks
Subjects	Machine learning--Industrial applications. Big data. Artificial intelligence--Industrial applications. Algorithms.

Series	Green engineering and technology: concepts and applications
Abstract	"Data science revolves around two giants, which are big data analytics and deep learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of big data along with deep learning systems. This book discusses how big data along with deep learning holds the potential to significantly increase data understanding and decision making. It also covers numerous applications in healthcare, education, communications, media, and the entertainment industry. The book offers innovative platforms for integrating big data and deep learning and presents issues related to adequate data store, sematic indexing, data tagging, and fast information retrieval. The audience includes industry professionals, academic professors, research scholars, system modelling, and simulation experts"-- Provided by publisher.
Bibliography note	Includes bibliographical references and index.
Access restriction	Available only to authorized users.
Technical details	Mode of access: World Wide Web
Source of description	Description based on print version record and CIP data provided by publisher.
Issued in other form	Print version: Integrating deep learning algorithms to overcome challenges in big data analytics Boca Raton : CRC Press, 2022 9780367466633
Genre/form	Electronic books.
LCCN	2021016674
ISBN	9781000454543 (epub)
ISBN	9781003038450 (ebk)
ISBN	(hbk)
ISBN	(pbk)

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Integrating deep learning algorithms to overcome challenges in big data analytics / edited by R. Sujatha, S.L. Aarthy, and R. Vettriselvan.

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