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020 _a9783031016851
024 7 _a10.1007/978-3-031-01685-1
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aQ335
_b2021 EB
100 1 _aWeiner, Joyce
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_9686792
245 1 0 _aWhy AI/Data Science Projects Fail :
_bHow to Avoid Project Pitfalls
_cby Joyce Weiner
250 _a1st edition 2021
264 1 _aCham
_bSpringer International Publishing
_c2021
300 _a1 recurso en línea (XI, 65 páginas)
336 _atexto
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
490 0 _aSynthesis Lectures on Computation and Analytics
_x2766-8967
505 0 _aPreface -- Introduction and Background -- Project Phases and Common Project Pitfalls -- Define Phase -- Making the Business Case: Assigning Value to Your Project -- Acquisition and Exploration of Data Phase -- Model-Building Phase -- Interpret and Communicate Phase -- Deployment Phase -- Summary of the five Methods to Avoid Common Pitfalls -- References -- Author Biography.
520 _aRecent data shows that 87% of Artificial Intelligence/Big Data projects don't make it into production (VB Staff, 2019), meaning that most projects are never deployed. This book addresses five common pitfalls that prevent projects from reaching deployment and provides tools and methods to avoid those pitfalls. Along the way, stories from actual experience in building and deploying data science projects are shared to illustrate the methods and tools. While the book is primarily for data science practitioners, information for managers of data science practitioners is included in the Tips for Managers sections.
988 _aSynthesis Collection of Technology_2021
650 7 _2embne
_9167300
_aGestión de proyectos
650 7 _2embne
_9495511
_aDatos masivos
650 7 _2embne
_aInteligencia artificial
_9413115
776 0 8 _iPrinted edition:
_z9783031000515
776 0 8 _iPrinted edition:
_z9783031005572
776 0 8 _iPrinted edition:
_z9783031028137
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01685-1
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _b02/2023
_dz
_esc
_zSI