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2024 | OriginalPaper | Buchkapitel

Deep Learning Techniques in Big Data Analytics

verfasst von : Ajay Kumar Badhan, Abhishek Bhattacherjee, Rita Roy

Erschienen in: Data Analytics and Machine Learning

Verlag: Springer Nature Singapore

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Abstract

The emergence of the digital age has ushered in an unprecedented era of data production and collection, creating big data models. In this context, a valuable technique to address complex issues originating from big data analytics is deep learning, which is a subgroup of machine learning. The aim of this chapter is to give a thorough assessment of deep learning methods and how they are implemented in big data analytics. Beginning with an introduction to the fundamental tents of deep learning, including neural networks and deep neural architectures, the mechanisms by which deep models can automatically learn and represent complex patterns from raw data are explored. It examines various aspects of deep learning applications of big data analysis. It shows how deep learning models excel in feature learning, enabling the automatic extraction of valuable information from huge data sets. Finally, the chapter describes emerging trends in deep learning and big data analysis, providing a glimpse into the future of this dynamic field. It draws attention to the pivotal role that deep learning techniques have played in transforming the big data analytics environment and emphasizes the ongoing significance of research and innovation in this quickly developing discipline.

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Metadaten
Titel
Deep Learning Techniques in Big Data Analytics
verfasst von
Ajay Kumar Badhan
Abhishek Bhattacherjee
Rita Roy
Copyright-Jahr
2024
Verlag
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-97-0448-4_9

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