Deep Learning For Big Data
Deep Learning for Big Data is a computational framework within machine learning that leverages deep neural architectures to automatically learn hierarchical representations from large-scale, high-dimensional, and often heterogeneous datasets, distinguishing itself by its capacity to process massive volumes of data with minimal human intervention while uncovering complex patterns across distributed data sources.
849
Publications
91.8K
Citations
3.2K
Authors
1.2K
Institutions
Publications per year
2017–2026
739
849
Deep learning applications and challenges in big data analytics
Maryam M. Najafabadi, Flavio Villanustre, Taghi M. Khoshgoftaar et al. · Journal Of Big Data · 2015 · 2.6K citations · Full text
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Dalian University of Technology
Dalian, China
15 h-index
38 publications
5.5K citations

Chinese Academy of Sciences
Beijing, China
13 h-index
32 publications
13.8K citations
Stanford University
Stanford, United States
12 h-index
52 publications
4.5K citations
Tsinghua University
Beijing, China
11 h-index
37 publications
4.1K citations

King Saud University
Riyadh, Saudi Arabia
10 h-index
21 publications
3.4K citations

University of Electronic Science and Technology of China
Chengdu, China
9 h-index
20 publications
5.3K citations
Florida Atlantic University
Boca Raton, United States
9 h-index
22 publications
13.4K citations
Vellore Institute of Technology University
Vellore, India
8 h-index
16 publications
1.6K citations
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Repository · 44 publications · 5.4K citations
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32 publications · 3.3K citations
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FGCS · 9 publications · 996 citations
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9 publications · 894 citations
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8 publications · 496 citations
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