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_c387186 _d387186 |
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| 001 | 387186 | ||
| 003 | ES-MaUEC | ||
| 005 | 20240111050230.0 | ||
| 006 | a||||fo|||| 00| 0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 220601s2021 sz | s |||| 0|eng d | ||
| 020 | _a9783031016851 | ||
| 024 | 7 |
_a10.1007/978-3-031-01685-1 _2doi |
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| 040 |
_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC |
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| 050 | 4 |
_aQ335 _b2021 EB |
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| 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 |
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| 337 |
_aelectrónico _bc _2rdamedia |
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| 338 |
_arecurso electrónico _bcr _2rdacarrier |
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| 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 |
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