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Enhance recommendations in Uber Eats with graph convolutional networks / Ankit Jain, Piero Molino.
Author
Jain, Ankit
[Browse]
Format
Video/Projected medium
Language
English
Published/Created
[Place of publication not identified] : O'Reilly, [2020]
Description
1 online resource.
Details
Subject(s)
Uber (Firm)
[Browse]
O'Reilly TensorFlow World (2019 Santa Clara, California)
[Browse]
TensorFlow
[Browse]
Customer services
—
Management
—
Data processing
[Browse]
Information visualization
[Browse]
Machine learning
[Browse]
On-screen presenter
Molino, Piero
[Browse]
Library of Congress genre(s)
Video recordings
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Series
Safari Books Online (Series)
[More in this series]
Summary note
"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.
Notes
Date of publication from resource description page.
Title from title screen (viewed July 27, 2020).
Copyright note
Copyright © O'Reilly Media, Incorporated.
Participant(s)/Performer(s)
Presenters, Ankit Jain, Piero Molino.
OCLC
1179144091
Other standard number
0636920373575
Statement on responsible collection description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
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Enhance recommendations in Uber Eats with graph convolutional networks / Ankit Jain, Piero Molino.
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