Big Data/Analytics.
Overview
| Works: | 21 works in 21 publications in 21 languages | |
|---|---|---|
Titles
Machine intelligence and big data in idustry[electronic resource] /
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Recent developments in intelligent information and database systems[electronic resource] /
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From curve fitting to machine learning[electronic resource] :an illustrative guide to scientific data analysis and computational intelligence /
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Business intelligence[electronic resource] :5th European Summer School, eBISS 2015, Barcelona, Spain, July 5-10, 2015 : tutorial lectures /
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Music similarity and retrieval[electronic resource] :an introduction to audio- and web-based strategies /
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Big data analytics[electronic resource] :a management perspective /
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Introducing the oscillations based paradigm[electronic resource] :the simulation of agents and social systems /
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Business information systems[electronic resource] :19th International Conference, BIS 2016, Leipzig, Germany, July, 6-8, 2016 : proceedings /
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Data stream management[electronic resource] :processing high-speed data streams /
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Anticipating future innovation pathways through large data analysis[electronic resource] /
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E-Life : Web-Enabled Convergence of Commerce, Work, and Social Life[electronic resource] :15th Workshop on e-Business, WEB 2015, Fort Worth, Texas, USA, December 12, 2015 : revised selected papers /
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Building trust in information[electronic resource] :perspectives on the frontiers of provenance /
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Healthcare and big data[electronic resource] :digital specters and phantom objects /
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Working with the American community survey in R[electronic resource] :a guide to using the acs package /
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Research and practical issues of enterprise information systems[electronic resource] :10th IFIP WG 8.9 Working Conference, CONFENIS 2016, Vienna, Austria, December 13-14, 2016 : proceedings /
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Data science[electronic resource] :create teams that ask the right questions and deliver real value /
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Quantitative analysis and IBM SPSS statistics[electronic resource] :a guide for business and finance /
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Advanced statistical methods in data science[electronic resource] /
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Large-scale graph processing using Apache Giraph[electronic resource] /
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Subjects