Description
Building LLM Applications for Production is a detailed textbook aimed at developers looking to enhance their skills in AI, particularly in the realm of Large Language Models (LLMs). The book provides an end-to-end resource for understanding and implementing LLMs in production environments. It covers essential topics such as prompting, fine-tuning, and retrieval-augmented generation (RAG), offering a roadmap to the future tech stack.
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The book is authored by Louis-François Bouchard and Louie Peters, with contributions from over ten experts at Towards AI, and curated by professionals from Activeloop, LlamaIndex, and Mila. It is designed for readers with an intermediate understanding of Python, aiming to guide them through creating production-ready LLM applications.
Spanning 463 pages, the book includes hands-on guides, code projects with real-world applications, and Colab notebooks for immediate practice. It also provides community access and an AI tutor to support learning. The content is structured to build understanding from the fundamentals of LLM theory to advanced techniques and frameworks.
Experts in the field have praised the book for its comprehensive coverage and practical insights. It serves as both an excellent primer for newcomers and a valuable reference for experienced practitioners. The book is available for purchase on Amazon, with options for new and used copies.
- CategoryOther AI Tools
Book Details
Comprehensive guide on LLMs
Includes prompting and fine-tuning techniques
Covers retrieval-augmented generation
Hands-on code projects
Real-world applications
Colab notebooks for practice
Community access
AI tutor support
Who This Book Is For
- AI Skill Enhancement
- LLM Application Development
- Python Programming
- Real-World Projects
- AI Community Engagement
