Cargando…
Ten things to know about ModelOps : successful strategies /
The past few years have seen significant developments in data science, AI, machine learning, and advanced analytics. But the wider adoption of these technologies has also brought greater cost, risk, regulation, and demands on organizational processes, tasks, and teams. This report explains how Model...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Sebastopol, CA :
O'Reilly Media, Inc.,
[2022]
|
| Edición: | First edition. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
| LEADER | 00000cam a22000007i 4500 | ||
|---|---|---|---|
| 001 | OR_on1325693391 | ||
| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
| 006 | m o d | ||
| 007 | cr cnu|||unuuu | ||
| 008 | 220607s2022 caua ob 000 0 eng d | ||
| 040 | |a ORMDA |b eng |e rda |e pn |c ORMDA |d OCLCF |d OCLCQ | ||
| 020 | |z 9781098133467 | ||
| 029 | 1 | |a AU@ |b 000072085951 | |
| 035 | |a (OCoLC)1325693391 | ||
| 037 | |a 9781098133474 |b O'Reilly Media | ||
| 050 | 4 | |a HF5548.2 | |
| 082 | 0 | 4 | |a 658/.05 |2 23/eng/20220607 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Hill, Thomas, |e author. | |
| 245 | 1 | 0 | |a Ten things to know about ModelOps : |b successful strategies / |c Thomas Hill, Mark Palmer & Larry Derany. |
| 250 | |a First edition. | ||
| 264 | 1 | |a Sebastopol, CA : |b O'Reilly Media, Inc., |c [2022] | |
| 300 | |a 1 online resource (41 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references. | ||
| 520 | |a The past few years have seen significant developments in data science, AI, machine learning, and advanced analytics. But the wider adoption of these technologies has also brought greater cost, risk, regulation, and demands on organizational processes, tasks, and teams. This report explains how ModelOps can provide both technical and operational solutions to these problems. Thomas Hill, Mark Palmer, and Larry Derany summarize important considerations, caveats, choices, and best practices to help you be successful with operationalizing AI/ML and analytics in general. Whether your organization is already working with teams on AI and ML, or just getting started, this report presents ten important dimensions of analytic practice and ModelOps that are not widely discussed, or perhaps even known. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Business |x Data processing. | |
| 650 | 0 | |a Artificial intelligence |x Industrial applications. | |
| 650 | 0 | |a Machine learning |x Industrial applications. | |
| 650 | 0 | |a Project management |x Technological innovations. | |
| 650 | 7 | |a Artificial intelligence |x Industrial applications. |2 fast |0 (OCoLC)fst00817262 | |
| 650 | 7 | |a Business |x Data processing. |2 fast |0 (OCoLC)fst00842293 | |
| 650 | 7 | |a Machine learning |x Industrial applications. |2 fast |0 (OCoLC)fst01004799 | |
| 700 | 1 | |a Palmer, Mark, |e author. | |
| 700 | 1 | |a Derany, Larry, |e author. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781098133474/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 994 | |a 92 |b IZTAP | ||