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📘 Title Name: LLM Engineer's Handbook: Master the Art of Engineering Large Language Models from Concept to Production
✍️ Authors: Paul Iusztin, Maxime Labonne
📦 Quality: White Paper Pakistan Print

🔹 Introduction:

LLM Engineer’s Handbook is a practical guide for anyone entering the rapidly expanding world of Large Language Models (LLMs). Written by experts Paul Iusztin and Maxime Labonne, this book walks readers through the complete lifecycle of building, training, optimizing, and deploying LLMs — from fundamental concepts to production-level engineering. Designed for beginners and practitioners, it blends theory with hands-on workflows and real-world best practices.

🔑 Key Points:

  • Explains core LLM concepts such as tokenization, embeddings, transformers, training pipelines, and evaluation.

  • Teaches practical model optimization techniques including quantization, fine-tuning, and deployment strategies.

  • Covers real engineering workflows for inference, scaling, monitoring, and serving LLMs in production environments.

  • Includes beginner-friendly examples and step-by-step instructions to build and deploy your own models.

  • Bridges the gap between theory and industry applications, making it ideal for aspiring AI/ML engineers.

🧠 Conclusion:

The LLM Engineer’s Handbook is an essential companion for beginners seeking mastery in modern AI. With clear explanations and practical engineering insights, it empowers readers to understand, build, refine, and deploy powerful language models confidently — from concept to production.

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