Master LLM Fine-Tuning
A Frontend Developer's Complete Guide to Training, Deploying, and Building Agents with Large Language Models
Created by 全Picture yourself confidently building and deploying your own fine-tuned language models, creating intelligent agents that solve real-world problems, and transitioning from frontend development into the cutting-edge world of AI engineering. This comprehensive guide transforms complex machine learning concepts into accessible, practical knowledge specifically designed for developers with frontend experience. You'll discover how to harness your existing programming skills while mastering the fundamentals of transformer architecture, attention mechanisms, and dataset preprocessing. Through hands-on examples and clear explanations, you'll learn to fine-tune open-source LLMs from scratch, understanding not just the how but the why behind each technique. The book covers everything from parameter-efficient fine-tuning methods to full model retraining, ensuring you can choose the right approach for your specific use case. Beyond training models, you'll master the art of deployment through robust serving APIs and learn to architect intelligent agents that can interact with external systems. Each chapter builds upon the previous one, creating a cohesive learning experience that takes you from LLM novice to confident practitioner. You'll gain the skills to evaluate model performance, optimize for different deployment scenarios, and troubleshoot common issues that arise in production environments. This isn't just another technical manual - it's your roadmap to becoming proficient in one of the most exciting areas of modern software development. By the end, you'll have the knowledge and confidence to build, deploy, and maintain your own LLM-powered applications and agent systems.
Est. Length
346 pages (20 chapters)
Language
English
Publication date
Oct 15, 2025
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