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A Quick View on Current Techniques and Machine Learning Algorithms for Big Data Analytics

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10.1109/ICTON.2016.7550517
 
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hdl:2117/103740

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Berral García, Josep LluísMés informacióMés informacióMés informació
Document typeConference report
Defense date2016
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
ProjectHi-EST - Holistic Integration of Emerging Supercomputing Technologies (EC-H2020-639595)
Abstract
Big-data is an excellent source of knowledge and information from our systems and clients, but dealing with such amount of data requires automation, and this brings us to data mining and machine leaming techniques. In the ICT sector, as in many other sectors of research and industry, platforms and tools are being served and developed in order to help professionals to treat their data and leam from it automatically ; most of those platforms coming from big companies like Google or Microsoft , or from incubators at the Apache Foundation. This brief review explains the basics of machine learning with sorne ICT examples, and enurnerates sorne (but not all) of the most used tools for analyzing and modelling big-data.
CitationBerral, J. A Quick View on Current Techniques and Machine Learning Algorithms for Big Data Analytics. A: International Conference on Transparent Optical Networks. "Proceedings of the 18th International Conference on Transparent Optical Networks (ICTON)". Trento: Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 1-4. 
URIhttp://hdl.handle.net/2117/103740
DOI10.1109/ICTON.2016.7550517
ISBN978-1-5090-1467-5
Publisher versionhttp://ieeexplore.ieee.org.recursos.biblioteca.upc.edu/stamp/stamp.jsp?arnumber=7550517
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