MASTERING LLMS FINE-TUNING: A COMPLETE GUIDE TO FINE-TUNING LLMS, LORA/QLORA WORKFLOWS, DATASET ENGINEERING, AND BUILDING PRODUCTION-READY AI MODELS WITH PYTHON & PYTORCH - Softcover
Synopsis
If you want to build custom LLMs that are faster, cheaper, smarter, and tailored for real business use cases — this is the book that shows you how.
The AI landscape is shifting fast. Companies no longer want generic chatbots — they want domain-specific, high-accuracy models fine-tuned for legal, medical, financial, engineering, and enterprise workflows. LLMs Fine-Tuning Mastery gives you everything you need to build these models with confidence.
This is the complete, practical handbook for engineers, data scientists, and AI builders who want to go beyond prompting and learn the engineering craft behind fine-tuning cutting-edge models using Python, PyTorch, Hugging Face Transformers, LoRA, QLoRA, and modern RAG pipelines.
Whether you’re building your first fine-tuned model or deploying a production-scale AI system, this book removes the guesswork and shows you exactly how to do it right.
Inside This Book, You Will Learn:
✔ How to Fine-Tune LLMs the Modern Way
SFT, instruction tuning, domain adaptation, alignment strategies, and continuous improvement loops.
✔ How to Use LoRA & QLoRA Like a ProSave 60–90% GPU memory while training models that match full fine-tuned performance.
✔ The Secrets of World-Class Dataset EngineeringCleaning, labeling, deduplication, quality scoring, data augmentation, synthetic data generation, and dataset management at scale.
✔ How to Build Production-Ready RAG SystemsImprove grounding, retrieval precision, and model reliability with advanced evaluation and optimization strategies.
✔ Deployment & Scaling Without the PainQuantization, inference optimization, GPU/CPU trade-offs, batching, caching, Triton/FastAPI servers, and observability patterns used in modern AI infra.
✔ End-to-End Architectures Used by Top AI TeamsConcrete workflows for managing experiments, validation, fine-tuning lifecycles, and delivering real value to users.
Who This Book Is For
AI/ML engineers who want to level up
Developers upgrading from prompt engineering to real model engineering
Data scientists breaking into LLM systems
Tech founders building AI-driven products
Anyone who wants to build custom models that actually perform in production
Why This Book Matters
Fine-tuning is the new competitive advantage.
Companies that master it will dominate their industries — because they can build models uniquely tailored to their data, their workflows, and their customers.
This book gives you the skills, patterns, and battle-tested best practices that real teams use to ship high-quality LLMs in the wild.
If you're serious about mastering this field, this is the guide you’ve been waiting for.
"synopsis" may belong to another edition of this title.
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Paperback. Condition: new. Paperback. If you want to build custom LLMs that are faster, cheaper, smarter, and tailored for real business use cases - this is the book that shows you how.The AI landscape is shifting fast. Companies no longer want generic chatbots - they want domain-specific, high-accuracy models fine-tuned for legal, medical, financial, engineering, and enterprise workflows. LLMs Fine-Tuning Mastery gives you everything you need to build these models with confidence.This is the complete, practical handbook for engineers, data scientists, and AI builders who want to go beyond prompting and learn the engineering craft behind fine-tuning cutting-edge models using Python, PyTorch, Hugging Face Transformers, LoRA, QLoRA, and modern RAG pipelines.Whether you're building your first fine-tuned model or deploying a production-scale AI system, this book removes the guesswork and shows you exactly how to do it right.Inside This Book, You Will Learn: How to Fine-Tune LLMs the Modern WaySFT, instruction tuning, domain adaptation, alignment strategies, and continuous improvement loops. How to Use LoRA & QLoRA Like a ProSave 60-90% GPU memory while training models that match full fine-tuned performance. The Secrets of World-Class Dataset EngineeringCleaning, labeling, deduplication, quality scoring, data augmentation, synthetic data generation, and dataset management at scale. How to Build Production-Ready RAG SystemsImprove grounding, retrieval precision, and model reliability with advanced evaluation and optimization strategies. Deployment & Scaling Without the PainQuantization, inference optimization, GPU/CPU trade-offs, batching, caching, Triton/FastAPI servers, and observability patterns used in modern AI infra. End-to-End Architectures Used by Top AI TeamsConcrete workflows for managing experiments, validation, fine-tuning lifecycles, and delivering real value to users.Who This Book Is ForAI/ML engineers who want to level upDevelopers upgrading from prompt engineering to real model engineeringData scientists breaking into LLM systemsTech founders building AI-driven productsAnyone who wants to build custom models that actually perform in productionWhy This Book MattersFine-tuning is the new competitive advantage.Companies that master it will dominate their industries - because they can build models uniquely tailored to their data, their workflows, and their customers.This book gives you the skills, patterns, and battle-tested best practices that real teams use to ship high-quality LLMs in the wild.If you're serious about mastering this field, this is the guide you've been waiting for. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798274928342
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