A Simple Guide to Retrieval Augmented Generation (Paperback)

Abhinav Kimoth

ISBN 10: 1633435857 / ISBN 13: 9781633435858

Verlag: Manning Publications, New York, 2025

Beschreibung

Paperback. Everything you need to know about Retrieval Augmented Generation in one human-friendly guide.Generative AI models struggle when you ask them about facts not covered in their training data. Retrieval Augmented Generationor RAGenhances an LLM's available data by adding context from an external knowledge base, so it can answer accurately about proprietary content, recent information, and even live conversations. RAG is powerful, and with A Simple Guide to Retrieval Augmented Generation, it's also easy to understand and implement!In A Simple Guide to Retrieval Augmented Generation you'll learn: The components of a RAG systemHow to create a RAG knowledge baseThe indexing and generation pipelineEvaluating a RAG systemAdvanced RAG strategiesRAG tools, technologies, and frameworks A Simple Guide to Retrieval Augmented Generation shows you how to enhance an LLM with relevant data, increasing factual accuracy and reducing hallucination. Your customer service chatbots can quote your company's policies, your teaching tools can draw directly from your syllabus, and your work assistants can access your organization's minutes, notes, and files. Everything you need to know about Retrieval Augmented Generation in one human-friendly guide. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Bestandsnummer des Verkäufers 9781633435858

Bibliografische Details

• Titel: A Simple Guide to Retrieval Augmented Generation (Paperback)
• Verlag: Manning Publications, New York
• Erscheinungsjahr: 2025
• Sprache: Englisch
• ISBN-10: 1633435857
• ISBN-13: 9781633435858
• Einband: Paperback
• Zustand: new

Über diesen Titel

Inhaltsangabe

Everything you need to know about Retrieval Augmented Generation in one human-friendly guide.

Generative AI models struggle when you ask them about facts not covered in their training data. Retrieval Augmented Generation―or RAG―enhances an LLM's available data by adding context from an external knowledge base, so it can answer accurately about proprietary content, recent information, and even live conversations. RAG is powerful, and with A Simple Guide to Retrieval Augmented Generation, it's also easy to understand and implement!

In A Simple Guide to Retrieval Augmented Generation you'll learn:

• The components of a RAG system
• How to create a RAG knowledge base
• The indexing and generation pipeline
• Evaluating a RAG system
• Advanced RAG strategies
• RAG tools, technologies, and frameworks

A Simple Guide to Retrieval Augmented Generation shows you how to enhance an LLM with relevant data, increasing factual accuracy and reducing hallucination. Your customer service chatbots can quote your company's policies, your teaching tools can draw directly from your syllabus, and your work assistants can access your organization's minutes, notes, and files.

Über die Autorin bzw. den Autor

Abhinav Kimothi is an entrepreneur and Vice President of Artificial Intelligence at Yarnit. He has spent over 15 years consulting and leadership roles in data science, machine learning and AI.