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Create Embeddings, Vector Search, and RAG with BigQuery

This course explores a Retrieval Augmented Generation (RAG) solution in BigQuery to mitigate AI hallucinations.

Google Cloud - Pluralsight course - Create Embeddings, Vector Search, and RAG with BigQuery
by Google Cloud

What you'll learn

This course explores a Retrieval Augmented Generation (RAG) solution in BigQuery to mitigate AI hallucinations. It introduces a RAG workflow that encompasses creating embeddings, searching a vector space, and generating improved answers. The course explains the conceptual reasons behind these steps and their practical implementation with BigQuery. By the end of the course, learners will be able to build a RAG pipeline using BigQuery and generative AI models like Gemini and embedding models to address their own AI hallucination use cases.

Table of contents

About the author

Google Cloud - Pluralsight course - Create Embeddings, Vector Search, and RAG with BigQuery
Google Cloud

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