profit through ML solutions to various LINE services 機械学習に関するLINE社内での標準化・⺠主化の推進 Lead standardization/democratization process of ML use at scale across LINE (inc. group companies) together w/ other data-related teams/depts. 「⼤量のデータが⽇々⽣成される」事業領域に注⼒ (⾳声, NLP, OCR, 画像など、特定ドメインに特化した専⾨組織も存在)
ML Platform LINE’S DATA PLATFORM LINEではどのようにサービス横断でのデータ活⽤を実現しているのか - LINE DEVELOPER DAY 2020 https://speakerdeck.com/line_devday2020/how-does-line-implement-cross-service-data-utilization?slide=11
Data Science Center Data Management Dept. Data Platform Dept. Other Depts. And Task Forces ML Privacy Team ML Solution Dept. ML&DS Planning team Other Depts. And Task Forces Data Management Team Data Management Team Data Management Team Data Management Team Data Management Team Data Platform Team ML Solution Team 1 ML Development Team ML Solution Team 2 ML Infrastructure Team ML Platform Dept. DSP ML Team Data Science Depts. • ML Platform Dept. • 事業横断的なPlatformを開発する組織 • ML Solution Dept. & ML&DS Planning team • 各事業と連携してMLの利活⽤を推進する組織
Science Center Other Depts. And Task Forces ML Privacy Team ML Solution Dept. ML&DS Planning team Other Depts. And Task Forces ML Solution Team 1 ML Development Team ML Solution Team 2 ML Infrastructure Team ML Platform Dept. DSP ML Team ML (and DS) Project & Product Management Recommender services, Demae-can, Image processing OA Optimization/Recommendation, User Persona / Feature Vector, LINE Music Ad Optimization (e.g. CTR prediction, etc.) ML R&D Activities (Diff. Privacy, Federated Learning, etc.) Recommender systems, ML Libraries, ML platform development, etc. ML infrastructure / platform design and DevOps • 2022/4/21現在で約40名が所属
(様々な組織が供給) 2. 最終的にコンテンツ or 広告を1つ選定 LINEではどのようにサービス横断でのデータ活⽤を実現しているのか - LINE DEVELOPER DAY 2020 https://speakerdeck.com/line_devday2020/how-does-line-implement-cross-service-data-utilization?slide=21 100 individual targeting logics for 1. 600k+ uniq. items / day 1B+ imps. / day
LINE DEVELOPER DAY 2020 https://speakerdeck.com/line_devday2020/how-does-line-implement-cross-service-data-utilization?slide=16 45 data types 3.6K dim. 960M users 45 data types 60M+ dim. 960M users
merchant deliver Demaecan order Upgrading the Food Delivery Service Using Machine Learning - LINE DEVELOPER DAY 2021 https://speakerdeck.com/line_devday2021/upgrading-the-food-delivery-service-using-machine-learning recommendation preparation time prediction shop arrival time prediction order dispatch order forecast