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A Simple Guide to Retrieval Augmented Generation
Everything you need to know about Retrieval Augmented Generation in one human-friendly guide.
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
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 gives an easy, yet comprehensive, introduction to RAG for AI beginners. You’ll go from basic RAG that uses indexing and generation pipelines, to modular RAG and multimodal data from images, spreadsheets, and more.
About the Book
A Simple Guide to Retrieval Augmented Generation is a plain-English guide to RAG. The book is easy to follow and packed with realistic Python code examples. It takes you concept-by-concept from your first steps with RAG to advanced approaches, exploring how tools like LangChain and Python libraries make RAG easy. And to make sure you really understand how RAG works, you’ll build a complete system yourself, even if you’re new to AI!
About the Author
Abhinav Kimothi is a seasoned data and AI professional. He has spent over 15 years in consulting and leadership roles in data science, machine learning and AI, and currently works as a Director of Data Science at Sigmoid.
PLEASE When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
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
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 gives an easy, yet comprehensive, introduction to RAG for AI beginners. You’ll go from basic RAG that uses indexing and generation pipelines, to modular RAG and multimodal data from images, spreadsheets, and more.
About the Book
A Simple Guide to Retrieval Augmented Generation is a plain-English guide to RAG. The book is easy to follow and packed with realistic Python code examples. It takes you concept-by-concept from your first steps with RAG to advanced approaches, exploring how tools like LangChain and Python libraries make RAG easy. And to make sure you really understand how RAG works, you’ll build a complete system yourself, even if you’re new to AI!
About the Author
Abhinav Kimothi is a seasoned data and AI professional. He has spent over 15 years in consulting and leadership roles in data science, machine learning and AI, and currently works as a Director of Data Science at Sigmoid.
PLEASE When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
- GenresArtificial Intelligence
Audible Audio
Published July 2, 2025
8 people are currently reading
9 people want to read
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Displaying 1 - 7 of 7 reviews
July 17, 2025
Navigating concepts like Retrieval-Augmented Generation (RAG), can be quite difficult. That is why I consider "A Simple Guide to Retrieval Augmented Generation" a brilliant beacon of clarity. If you want to genuinely understand and even implement RAG, this book is an absolute must-read.
What truly struck me is the author's remarkable ability to distill profoundly complex topics into simple, digestible terms. Technical concepts that usually require multiple re-reads became intuitively clear on the very first pass. That, for me, was a game-changer.
The author masterfully navigates RAG's nuances, breaking down its architecture and applications with an engaging style.
Beyond its impressive teaching approach, I found the book to be a truly practical resource. It is more than just a book; it's an invaluable educational tool. It's a clear testament to the author's deep expertise and exceptional communication talent. For anyone intimidated by modern AI, or simply seeking the clearest explanation of RAG, this guide is an indispensable addition. It is, without a doubt, an outstanding achievement.
What truly struck me is the author's remarkable ability to distill profoundly complex topics into simple, digestible terms. Technical concepts that usually require multiple re-reads became intuitively clear on the very first pass. That, for me, was a game-changer.
The author masterfully navigates RAG's nuances, breaking down its architecture and applications with an engaging style.
Beyond its impressive teaching approach, I found the book to be a truly practical resource. It is more than just a book; it's an invaluable educational tool. It's a clear testament to the author's deep expertise and exceptional communication talent. For anyone intimidated by modern AI, or simply seeking the clearest explanation of RAG, this guide is an indispensable addition. It is, without a doubt, an outstanding achievement.
August 16, 2025
Absolutely loved this book! As someone who uses RAG applications every day, I found it to be an incredibly practical and clear guide. The explanations are easy to follow, and the diagrams make even complex concepts simple to grasp. I keep coming back to this book as both a reference and a teaching resource. Highly recommend it to anyone looking to truly understand RAG from the ground up whether you’re a beginner or experienced practitioner. Thank you, Abhinav, for creating such a helpful resource!
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July 16, 2025This book offers an excellent introduction to the world of Generation Augmented Retrieval (GAR), a technology that has constantly evolved and continues to incorporate new implementation methods. It is especially useful for those looking to develop AI-based chatbot systems and need to minimize model-generated hallucinations. It is definitely a highly recommended read for anyone getting started in this innovative field.
July 16, 2025
I have worked on RAG systems and I found this valuable because it goes beyond the "basics" and tackles practical, real-world topics. At the same time, it can be used as a refresher/reference as well since it's very well structured. Don't be fooled by the "Simple" in the title - it is fairly exhaustive, but explained in clear, organized (and hence, simple) way.
August 28, 2025
Excellent introductory book. Easy to read and well organized. The book not only introduces the RAG framework, but also shows future path for learning.
October 1, 2025
read half of it and it was enough. helped me understand how RAG works in theory as a complete beginner. unfortunately, the code was very confusing for me since it wasn't really explained
Displaying 1 - 7 of 7 reviews