Titlebook: Deep Learning: Convergence to Big Data Analytics; Murad Khan,Bilal Jan,Haleem Farman Book 2019 The Author(s), under exclusive license to S

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Book 2019rstanding 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

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Das Variationsspektrum des Deutschenorough study of the big data analytics and the tools required to process the big data is also presented with reference to some existing and well-known work. Further, the chapter is concluded by connecting the deep learning with big data analytics for filling the gap of using machine learning for huge datasets.

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https://doi.org/10.1007/978-3-476-04921-6 application of BD, BD analytical tools, and data types of BD are described, in order to enlighten the readers about this broad subject domain. Finally, the chapter concludes by identifying potential opportunities as well as challenges faced by BD and BDA.

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Big Data Analytics, application of BD, BD analytical tools, and data types of BD are described, in order to enlighten the readers about this broad subject domain. Finally, the chapter concludes by identifying potential opportunities as well as challenges faced by BD and BDA.

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2191-5768 chniques 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 var978-981-13-3458-0978-981-13-3459-7Series ISSN 2191-5768 Series E-ISSN 2191-5776

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Book 2019arning, 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 var

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