Deep Learning: Convergence to Big Data Analytics

This book presents deep learning techniques, concepts, and algorithms to classify and analyze big data. Further, it offers an introductory level understanding of the new programming languages and tools used to analyze big data in real-time, such as Hadoop, SPARK, and GRAPHX. Big data analytics using...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Khan, Murad (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Jan, Bilal (http://id.loc.gov/vocabulary/relators/aut), Farman, Haleem (http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2019.
Έκδοση:1st ed. 2019.
Σειρά:SpringerBriefs in Computer Science,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
LEADER 04336nam a2200553 4500
001 978-981-13-3459-7
003 DE-He213
005 20191027051640.0
007 cr nn 008mamaa
008 181230s2019 si | s |||| 0|eng d
020 |a 9789811334597  |9 978-981-13-3459-7 
024 7 |a 10.1007/978-981-13-3459-7  |2 doi 
040 |d GrThAP 
050 4 |a QA76.9.D3 
072 7 |a UN  |2 bicssc 
072 7 |a COM021000  |2 bisacsh 
072 7 |a UN  |2 thema 
072 7 |a UMT  |2 thema 
082 0 4 |a 005.74  |2 23 
100 1 |a Khan, Murad.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Deep Learning: Convergence to Big Data Analytics  |h [electronic resource] /  |c by Murad Khan, Bilal Jan, Haleem Farman. 
250 |a 1st ed. 2019. 
264 1 |a Singapore :  |b Springer Singapore :  |b Imprint: Springer,  |c 2019. 
300 |a XVI, 79 p. 27 illus., 18 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a SpringerBriefs in Computer Science,  |x 2191-5768 
505 0 |a Chapter 1. Introduction -- Chapter 2. Big Data Analytics -- Chapter 3. Deep Learning Methods and Applications -- Chapter 4. Integration of Big Data and Deep Learning -- Chapter 5. Future Aspects. . 
520 |a This book presents deep learning techniques, concepts, and algorithms to classify and analyze big data. Further, it offers an introductory level understanding of the new programming languages and tools used to analyze big data in real-time, such as Hadoop, SPARK, and GRAPHX. Big data analytics using traditional techniques face various challenges, such as fast, accurate and efficient processing of big data in real-time. In addition, the Internet of Things is progressively increasing in various fields, like smart cities, smart homes, and e-health. As the enormous number of connected devices generate huge amounts of data every day, we need sophisticated algorithms to deal, organize, and classify this data in less processing time and space. Similarly, existing techniques and algorithms for deep learning in big data field have several advantages thanks to the two main branches of the deep learning, i.e. convolution and deep belief networks. This book offers insights into these techniques and applications based on these two types of deep learning. Further, it helps students, researchers, and newcomers understand big data analytics based on deep learning approaches. It also discusses various machine learning techniques in concatenation with the deep learning paradigm to support high-end data processing, data classifications, and real-time data processing issues. The classification and presentation are kept quite simple to help the readers and students grasp the basics concepts of various deep learning paradigms and frameworks. It mainly focuses on theory rather than the mathematical background of the deep learning concepts. The book consists of 5 chapters, beginning with an introductory explanation of big data and deep learning techniques, followed by integration of big data and deep learning techniques and lastly the future directions. 
650 0 |a Database management. 
650 0 |a Artificial intelligence. 
650 0 |a Data structures (Computer science). 
650 0 |a Big data. 
650 1 4 |a Database Management.  |0 http://scigraph.springernature.com/things/product-market-codes/I18024 
650 2 4 |a Artificial Intelligence.  |0 http://scigraph.springernature.com/things/product-market-codes/I21000 
650 2 4 |a Data Structures.  |0 http://scigraph.springernature.com/things/product-market-codes/I15017 
650 2 4 |a Big Data.  |0 http://scigraph.springernature.com/things/product-market-codes/I29120 
700 1 |a Jan, Bilal.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Farman, Haleem.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9789811334580 
776 0 8 |i Printed edition:  |z 9789811334603 
830 0 |a SpringerBriefs in Computer Science,  |x 2191-5768 
856 4 0 |u https://doi.org/10.1007/978-981-13-3459-7  |z Full Text via HEAL-Link 
912 |a ZDB-2-SCS 
950 |a Computer Science (Springer-11645)