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Lessons Learned Running RL Recommendation at Scale in Physical Retail Setting at Starbucks

On Demand

Type

  • Session

フォーマット

  • Virtual

Track

  • Industry and Business Use Cases

Difficulty

  • Intermediate

Duration

  • 40 min

概要

Change in QSR state from static boards to dynamic and contextualized recommendation. The brain behind the system connects the Starbucks brand and culture with state-of-the-art AI techniques. Review some of the tactics and lessons learnt by running an RL algorithm and deep item collaborative filtering in production over a year.

Session Speakers

Sulbha Jain

Sr. Data Scientist

スターバックス

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