In diesem Kurs wird eine Lösung für Retrieval-Augmented Generation (RAG) in BigQuery vorgestellt, die KI-Halluzinationen minimiert. Sie lernen einen RAG-Workflow kennen, der die Erstellung von Einbettungen, die Suche in einem Vektorraum und die Generierung verbesserter Antworten umfasst. Darüber hinaus werden die konzeptionellen Gründe für diese Schritte und ihre praktische Umsetzung mit BigQuery erklärt. Am Ende des Kurses werden Sie in der Lage sein, eine RAG-Pipeline mithilfe von BigQuery und generativen KI-Modellen wie Gemini zu erstellen und Modelle einzubetten, um KI-Halluzinationen zu verhindern.

Einbettungen, Vektorsuche und RAG mit BigQuery erstellen
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Einbettungen, Vektorsuche und RAG mit BigQuery erstellen

Instructor: Google Cloud Training
Included with
Gain insight into a topic and learn the fundamentals.
Advanced level
Designed for those already in the industry
2 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Einbettungen durch Verwendung entsprechender Modelle mit BigQuery generieren
Vektorsuche in BigQuery durchführen und den Prozess nachvollziehen
RAG-Pipeline mit BigQuery erstellen
Skills you'll gain
Tools you'll learn
Details to know

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Assessments
1 assignment
Taught in German
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There is 1 module in this course
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