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Best in 7 days
Best in 7 days
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Best in 7 days
4.1 ★★★★★
Based on 776 reviews
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Product Reviews
★★★★★ 5
Excellent roadmap for the local AI jungle
Format: Paperback
Great little book.
Every page has something useful. No fluff. Clearly written by someone whose been in the trenches lol
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Reviewed in the United States on September 23, 2025
★★★★★ 5
Great primer for building LLM Applications
Format: Kindle
I highly recommend the book for anyone who wants to come up to speed on running Ollama for open models. The book is well structure and teach you how to create a working RAG Application. I recommend as a primer for anyone interested in building LLM Applications.
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Reviewed in the United States on May 5, 2025
★★★★★ 5
Breaks down complex concepts into bite-sized, practical chapters.
Format: Kindle
This hands-on guide to Ollama is exactly what I needed! The author breaks down complex concepts into bite-sized, practical chapters that get straight to the point. The sections on different Ollama models and customization were particularly helpful. If you're looking to learn about building local LLM-powered applications without any fluff, this book is a great investment.
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Reviewed in the United States on February 21, 2025
★★★★★ 5
Great helpful book.
Format: Kindle
This book is simple to follow, Greg gets back to you in a very timely manner. I have bought other books from Greg and they are always very helpful.
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Reviewed in the United States on February 21, 2025
★★★★★ 5
Love it - revolutionary approach to teaching, presenting complex concepts
Format: Paperback
This book is a game-changer for neural networks and AI enthusiasts. It takes a revolutionary approach to teaching, presenting complex concepts in a simple and engaging manner. The book is filled with colorful diagrams and illustrations that make learning accessible and enjoyable. I’ve read several other books, but this one stands out. It’s not a beginner’s guide, but once you grasp the early concepts, it takes you to a whole new level of understanding. I will give it 10 stars if I could.
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Reviewed in the United States on June 18, 2025
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