Encyclopedia of Big Data Technologies

Living Edition
| Editors: Sherif Sakr, Albert Zomaya

Deep Learning on Big Data

  • Gianluigi FolinoEmail author
  • Massimo Guarascio
  • Maryam A. Haeri
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-63962-8_307-1


Deep Learning is a family of machine learning methods based on the composition of multiple (simple) processing layers, in order to learn complex (nonlinear) functions, which can be used to cope with many challenging application scenarios (e.g., Computer Vision, Natural Language Processing, Speech Recognition and Genomics (Le Cun et al. 2015)).


In the last few years, advances in digital sensors, computation, communications, and storage technologies and the large diffusion of IoT devices facilitated the production of huge collections of heterogeneous data, which are also susceptible to rapid changes over time. The term Big Data is used to define this kind of phenomenon (Wu et al. 2014).

Deep learning (DL) includes a wide range of machine learning techniques that aims at training artificial neural networks (ANNs) composed of a large number of hidden layers. These methods have been effectively used to tackle different types of problems (e.g., Computer Vision, Natural...

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Gianluigi Folino
    • 1
    Email author
  • Massimo Guarascio
    • 1
  • Maryam A. Haeri
    • 2
  1. 1.ICAR-CNR (Institute for High Performance Computing and Networks, National Research Council)RendeItaly
  2. 2.Department of Computer Engineering and Information TechnologyAmirkabir University of TechnologyTehranIran

Section editors and affiliations

  • Domenico Talia
  • Paolo Trunfio
    • 1
  1. 1.DIMESUniversity of CalabriaRendeItaly