このコースでは、BigQuery で検索拡張生成（RAG）ソリューションを使用して AI ハルシネーションを軽減する方法を説明します。エンベディングの作成、ベクトル空間の検索、改善された回答の生成を含む RAG ワークフローについて解説し、これらの手順の背後にある概念的な理由と、BigQuery を使用した実践的な実装方法についても説明します。このコースを完了すると、BigQuery、Gemini などの生成 AI モデル、エンベディング モデルを使用して RAG パイプラインを構築し、独自の AI ハルシネーションのユースケースに対処できるようになります。
エンベディング作成、ベクトル検索、BigQuery での RAG
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2 hours to complete
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What you'll learn
BigQuery でエンベディング モデルを使用し、エンベディングを生成する。
BigQuery でベクトル検索を行い、そのプロセスを理解する。
BigQuery を使用して RAG（検索拡張生成）パイプラインを作成する。
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Taught in Japanese
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