August 2026
Intermediate to advanced
552 pages
8h 9m
Japanese
Content preview from Google CloudではじめるAI/ML入門 ―ハンズオンで学ぶデータ基盤、分析、エージェント開発Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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17章Agent Platform Feature Storeによる特徴量管理
17.1 はじめに
本章の内容を学習することで、機械学習モデルの学習時と推論時で特徴量の不整合（Training-Serving Skew）が発生する問題を構造的に防止できるようになります。特徴量を一元管理することで、学習パイプラインと推論パイプラインの両方から同じデータソースを参照する堅牢な特徴量基盤を構築できます。さらに、Feature Monitoringによる特徴量の分布変化（データドリフト）の検出手法を習得することで、本番環境でのモデル品質の継続的な維持が可能になります。
- この章の内容
- Training-Serving Skewとドリフトの課題整理
- Agent Platform Feature Store（旧称：Vertex AI Feature Store）のアーキテクチャと構成要素
- BigQueryデータソースからの特徴量設計
- FeatureOnlineStore / FeatureGroup / FeatureViewの構築
- スケジュール同期と継続的同期によるデータ反映
- ポイントインタイム（PIT）取得による学習データ作成
- Online Serving APIによる推論時の特徴量取得
- Feature Monitoringによるドリフト検出と監視
第Ⅰ部では、Agent Platformを使った機械学習パイプラインの構築方法を学びました。しかし、モデルを本番運用する上では「特徴量をどう管理するか」という課題が残っています。学習時と推論時で特徴量の計算ロジックや値にズレがあれば、モデルの予測精度は次第に劣化していきます。こうした問題へ対処するために生まれたのが、特徴量を一元管理する仕組みである ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.