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Search logs + machine learning = autotagged inventory /
"For ecommerce applications, matching users with the items they want is the name of the game. If they can't find what they want, then how can they buy anything? John Berryman takes a deep dive into the problem space and Eventbrite's approach. He explores how the company gathered train...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor Corporativo: | |
| Formato: | Electrónico Congresos, conferencias Video |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified] :
O'Reilly Media,
2020.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Berryman, John, |d 1980- |e on-screen presenter. | |
| 245 | 1 | 0 | |a Search logs + machine learning = |b autotagged inventory / |c John Berryman. |
| 246 | 3 | |a Search logs plus machine learning equals autotagged inventory | |
| 264 | 1 | |a [Place of publication not identified] : |b O'Reilly Media, |c 2020. | |
| 300 | |a 1 online resource (1 streaming video file (37 min., 40 sec.)) | ||
| 336 | |a two-dimensional moving image |b tdi |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 337 | |a video |b v |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 500 | |a Title from resource description page (viewed July 21, 2020). | ||
| 511 | 0 | |a Presenter, John Barryman. | |
| 520 | |a "For ecommerce applications, matching users with the items they want is the name of the game. If they can't find what they want, then how can they buy anything? John Berryman takes a deep dive into the problem space and Eventbrite's approach. He explores how the company gathered training data from its search and click logs, and how it built and refined the model. You'll see the output of the model and both the positive results of Eventbrite's work, as well as the work left to be done. You'll leave with some new ideas to take back to your business."--Resource description page | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Electronic data processing |v Congresses. | |
| 650 | 0 | |a Data structures (Computer science) |v Congresses. | |
| 650 | 0 | |a Cloud computing |v Congresses. | |
| 650 | 0 | |a Artificial intelligence |v Congresses. | |
| 650 | 6 | |a Structures de données (Informatique) |v Congrès. | |
| 650 | 6 | |a Infonuagique |v Congrès. | |
| 650 | 6 | |a Intelligence artificielle |v Congrès. | |
| 650 | 7 | |a Artificial intelligence |2 fast |0 (OCoLC)fst00817247 | |
| 650 | 7 | |a Cloud computing |2 fast |0 (OCoLC)fst01745899 | |
| 650 | 7 | |a Data structures (Computer science) |2 fast |0 (OCoLC)fst00887978 | |
| 650 | 7 | |a Electronic data processing |2 fast |0 (OCoLC)fst00906956 | |
| 655 | 7 | |a Conference papers and proceedings |2 fast |0 (OCoLC)fst01423772 | |
| 711 | 2 | |a O'Reilly Strata Data Conference |d (2019 : |c New York, N.Y.) |j issuing body. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/videos/~/0636920372349/?ar |z Texto completo (Requiere registro previo con correo institucional) |
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