Guide to Retrieval Augmented Generation (RAG) for Practitioners

This e-book offers an overview of Retrieval Augmented Generation (RAG), a technique for enhancing large language models (LLMs) with external data. RAG combines an LLM's capabilities with retrieving context from a vector database, improving response accuracy and currency.

It includes RAG use cases, from question-answering to content generation, and a step-by-step RAG implementation guide.

Learn how RAG, combined with methods like prompt engineering and fine-tuning, enhances AI applications. Download the full e-book now.

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Vendor:: DataBricks
Posted:: Nov 8, 2024
Published:: Nov 9, 2024
Format:: HTML
Type:: eBook

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