Machine Learning Design Patterns in Industry

• Item type: Symposium(1)
• 公開日: 2021-08-30
• タイトル: Machine Learning Design Patterns in Industry
• タイトル / 言語: en
• タイトル: Machine Learning Design Patterns in Industry
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: 基調講演
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_5794
• 資源タイプ: conference paper
• 著者所属: Google
• 著者所属(英): en
• 著者所属(英): Google
• 著者名: Valliappa, Lakshmanan
• 著者名(英): Valliappa, Lakshmanan
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Design patterns are formalized best practices to solve common problems when designing a software system. As machine learning moves from being a research discipline to a software one, it is useful to catalog tried-and-proven methods to help engineers tackle frequently occurring problems that crop up during the ML process. In this talk, I will cover five patterns (Hashed Feature, Neutral Class, Stateless Serving Function, Bridged Schema, Feature Store) that academic researchers often don’t think about but are very useful in practical situations that arise in industry. For data scientists and ML engineers, these patterns provide a way to apply hard-won knowledge from hundreds of ML experts to your own projects.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Design patterns are formalized best practices to solve common problems when designing a software system. As machine learning moves from being a research discipline to a software one, it is useful to catalog tried-and-proven methods to help engineers tackle frequently occurring problems that crop up during the ML process. In this talk, I will cover five patterns (Hashed Feature, Neutral Class, Stateless Serving Function, Bridged Schema, Feature Store) that academic researchers often don’t think about but are very useful in practical situations that arise in industry. For data scientists and ML engineers, these patterns provide a way to apply hard-won knowledge from hundreds of ML experts to your own projects.
• 書誌情報: ソフトウェアエンジニアリングシンポジウム2021論文集; 巻 2021, p. 12-12, 発行日 2021-08-30
• 出版者 / 言語: ja
• 出版者: 情報処理学会