PacktPublishing/LLM-Engineers-Handbook
The LLM's practical guide: From the fundamentals to deploying advanced LLM and RAG apps to AWS using LLMOps best practices
This handbook helps AI engineers and machine learning practitioners build, train, and deploy custom Large Language Model (LLM) and Retrieval Augmented Generation (RAG) applications. It guides you through the entire lifecycle, from data collection and model training to robust AWS deployment and monitoring. You'll learn to take raw data and turn it into a production-ready LLM system that solves real-world problems.
4,823 stars.
Use this if you are an AI engineer or ML practitioner looking for a practical, end-to-end guide to building and deploying advanced LLM and RAG applications, especially to AWS.
Not ideal if you are looking for a conceptual overview of LLMs without practical implementation details or if you are not interested in deploying models to cloud environments like AWS.
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Python
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MIT
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Last pushed
Mar 02, 2026
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