Abstract
Analytics at the Fog server enables fast processing of incoming data for real-time response to IoT devices that generate the date. This chapter explores the research issues involved in the application of traditional shallow machine learning and also Deep Learning techniques to Big Data analytics. It surveys global advances in research in extending conventional unsupervised and semi-supervised algorithms and association rule mining algorithms to Big Data scenarios. Further, it discusses the Deep Learning applications of Big Data analytics to fields of computer vision, speech processing and text processing, such as semantic indexing and data tagging.
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© 2019 Springer Nature Singapore Pte Ltd.
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Prabhu, C.S.R. (2019). Fog Analytics. In: Fog Computing, Deep Learning and Big Data Analytics-Research Directions. Springer, Singapore. https://doi.org/10.1007/978-981-13-3209-8_3
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DOI: https://doi.org/10.1007/978-981-13-3209-8_3
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Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-3208-1
Online ISBN: 978-981-13-3209-8
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