Enhance recommendations in Uber Eats with graph convolutional networks:
"Uber Eats has become synonymous with online food ordering. With an increasing selection of restaurants and dishes in the app, personalization is quite crucial to drive growth. One aspect of personalization is a better recommendation of restaurants and dishes so users can get the right food at...
Gespeichert in:
| Beteilige Person: | |
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| Weitere beteiligte Personen: | |
| Format: | Elektronisch Video |
| Sprache: | Englisch |
| Veröffentlicht: |
[Place of publication not identified]
O'Reilly
[2020]
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| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/0636920373575/?ar |
| Zusammenfassung: | "Uber Eats has become synonymous with online food ordering. With an increasing selection of restaurants and dishes in the app, personalization is quite crucial to drive growth. One aspect of personalization is a better recommendation of restaurants and dishes so users can get the right food at the right time. Ankit Jain and Piero Molino (Uber AI Labs) detail how to augment the ranking models with better representations of users, dishes, and restaurants. Specifically, they leverage the graph structure of Uber Eats data to learn node embeddings of various entities using state-of-the-art graph convolutional networks implemented in TensorFlow and how these methods perform better than standard matrix factorization approaches for this use case." Recorded at the O'Reilly TensorFlow World conference, October 28-31, 2019, Santa Clara, CA.--Resource description page |
| Beschreibung: | Title from title screen (viewed July 27, 2020). - Date of publication from resource description page |
| Umfang: | 1 Online-Ressource (1 streaming video file (39 min., 27 sec.)) |
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| spelling | Jain, Ankit VerfasserIn aut Enhance recommendations in Uber Eats with graph convolutional networks Ankit Jain, Piero Molino [Place of publication not identified] O'Reilly [2020] 1 Online-Ressource (1 streaming video file (39 min., 27 sec.)) zweidimensionales bewegtes Bild tdi rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Title from title screen (viewed July 27, 2020). - Date of publication from resource description page "Uber Eats has become synonymous with online food ordering. With an increasing selection of restaurants and dishes in the app, personalization is quite crucial to drive growth. One aspect of personalization is a better recommendation of restaurants and dishes so users can get the right food at the right time. Ankit Jain and Piero Molino (Uber AI Labs) detail how to augment the ranking models with better representations of users, dishes, and restaurants. Specifically, they leverage the graph structure of Uber Eats data to learn node embeddings of various entities using state-of-the-art graph convolutional networks implemented in TensorFlow and how these methods perform better than standard matrix factorization approaches for this use case." Recorded at the O'Reilly TensorFlow World conference, October 28-31, 2019, Santa Clara, CA.--Resource description page Uber (Firm) O'Reilly TensorFlow World Santa Clara, Calif.) (2019 TensorFlow Customer services Management Data processing Information visualization Machine learning Service à la clientèle ; Gestion ; Informatique Visualisation de l'information Apprentissage automatique Electronic videos Molino, Piero MitwirkendeR ctb |
| spellingShingle | Jain, Ankit Enhance recommendations in Uber Eats with graph convolutional networks Uber (Firm) O'Reilly TensorFlow World Santa Clara, Calif.) (2019 TensorFlow Customer services Management Data processing Information visualization Machine learning Service à la clientèle ; Gestion ; Informatique Visualisation de l'information Apprentissage automatique Electronic videos |
| title | Enhance recommendations in Uber Eats with graph convolutional networks |
| title_auth | Enhance recommendations in Uber Eats with graph convolutional networks |
| title_exact_search | Enhance recommendations in Uber Eats with graph convolutional networks |
| title_full | Enhance recommendations in Uber Eats with graph convolutional networks Ankit Jain, Piero Molino |
| title_fullStr | Enhance recommendations in Uber Eats with graph convolutional networks Ankit Jain, Piero Molino |
| title_full_unstemmed | Enhance recommendations in Uber Eats with graph convolutional networks Ankit Jain, Piero Molino |
| title_short | Enhance recommendations in Uber Eats with graph convolutional networks |
| title_sort | enhance recommendations in uber eats with graph convolutional networks |
| topic | Uber (Firm) O'Reilly TensorFlow World Santa Clara, Calif.) (2019 TensorFlow Customer services Management Data processing Information visualization Machine learning Service à la clientèle ; Gestion ; Informatique Visualisation de l'information Apprentissage automatique Electronic videos |
| topic_facet | Uber (Firm) O'Reilly TensorFlow World Santa Clara, Calif.) (2019 TensorFlow Customer services Management Data processing Information visualization Machine learning Service à la clientèle ; Gestion ; Informatique Visualisation de l'information Apprentissage automatique Electronic videos |
| work_keys_str_mv | AT jainankit enhancerecommendationsinubereatswithgraphconvolutionalnetworks AT molinopiero enhancerecommendationsinubereatswithgraphconvolutionalnetworks |