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020 _a9783030373092
024 7 _a10.1007/978-3-030-37309-2
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
041 0 _aeng
050 4 _aQA76.9.B45
_b2020 EB
245 0 0 _aData Science :
_bFrom Research to Application
_cedited by Mahdi Bohlouli, Bahram Sadeghi Bigham, Zahra Narimani, Mahdi Vasighi, Ebrahim Ansari
250 _aFirst data
264 1 _aCham
_bSpringer International Publishing :
_bImprint Springer
_c2020
300 _a1 recurso en línea (XI, 338 páginas)
_b125 ilustraciones, 83 ilustraciones a color
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _atext file
_bPDF
490 0 _aLecture Notes on Data Engineering and Communications Technologies
_x2367-4512
_v45
490 0 _aIntelligent Technologies and Robotics (Springer-42732)
505 0 _aEfficient Cluster Head Selection using the Non-Linear Programming Method for Wireless Sensor Networks -- A New Distributed Ensemble Method with Applications to Machine Learning -- Forecasting Multivariate Time-Series Data Using LSTM and Mini-Batches -- Forecasting of Customer Behavior using Time Series Analysis -- Using Augmented Genetic Algorithm for Search-Based Software Testing -- A Novel Topological Descriptor for ASL -- Extracting Cellphone users' Stay Locations by Multiple-Steps Clustering Approach.
520 3 _aThis book presents outstanding theoretical and practical findings in data science and associated interdisciplinary areas. Its main goal is to explore how data science research can revolutionize society and industries in a positive way, drawing on pure research to do so. The topics covered range from pure data science to fake news detection, as well as Internet of Things in the context of Industry 4.0. Data science is a rapidly growing field and, as a profession, incorporates a wide variety of areas, from statistics, mathematics and machine learning, to applied big data analytics. According to Forbes magazine, "Data Science" was listed as LinkedIn's fastest-growing job in 2017. This book presents selected papers from the International Conference on Contemporary Issues in Data Science (CiDaS 2019), a professional data science event that provided a real workshop (not "listen-shop") where scientists and scholars had the chance to share ideas, form new collaborations, and brainstorm on major challenges; and where industry experts could catch up on emerging solutions to help solve their concrete data science problems. Given its scope, the book will benefit not only data scientists and scientists from other domains, but also industry experts, policymakers and politicians.
988 _aPrimersemestre_2020_Robotics
650 7 _2embne
_9495511
_aDatos masivos
650 7 _2embne
_aInformática
_9139268
700 1 _aBohlouli, Mahdi.
_eeditor
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aSadeghi Bigham, Bahram.
_eeditor
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aNarimani, Zahra.
_eeditor
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_984785
700 1 _aVasighi, Mahdi.
_eeditor
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aAnsari, Ebrahim.
_eeditor
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783030373085
776 0 8 _iPrinted edition:
_z9783030373108
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-37309-2
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
_n0
998 _b03/2020
_dz
_eb
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