Case Studies in Amalgamation of Deep Learning and Big Data

View Sample PDF

Author(s): Balajee Jeyakumar (VIT University, India), M.A. Saleem Durai (VIT University, India)and Daphne Lopez (VIT University, India)
Copyright: 2020
Pages: 13
Source title: Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-0414-7.ch054

Keywords: Artificial Intelligence / Computer Science & IT / Engineering Science Reference / Neural Networks

Purchase

View Case Studies in Amalgamation of Deep Learning and Big Data on the publisher's website for pricing and purchasing information.

Abstract

Deep learning is now more popular research domain in machine learning and pattern recognition in the world. It is widely success in the far-reaching area of applications such as Speech recognition, Computer vision, Natural language processing and Reinforcement learning. With the absolute amount of data accessible nowadays, big data brings chances and transformative possible for several sectors, on the other hand, it also performs on the unpredicted defies to connecting data and information. The size of the data is getting larger, and deep learning is imminent to play a vital role in big data predictive analytics solutions. In this paper, we make available a brief outline of deep learning and focus recent research efforts and the challenges in the fields of science, medical and water resource system.

The IRMA Community

Research IRM

Case Studies in Amalgamation of Deep Learning and Big Data

Purchase

Abstract

Related Content

IRMA Sponsors