Fine-Tuning and Alignment Engineering: LoRA, DPO, RLHF, and Domain Adaptation for Production LLMs - Couverture souple

Livre 18 sur 19: Production AI Engineering Series

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9798185127865: Fine-Tuning and Alignment Engineering: LoRA, DPO, RLHF, and Domain Adaptation for Production LLMs

Synopsis

Master the Art of Customizing LLMs for Production

In the rapidly evolving world of artificial intelligence, building generic models is no longer enough. Fine-Tuning and Alignment Engineering is your comprehensive, hands-on guide to taking pre-trained large language models and tailoring them to deliver enterprise-grade performance, safety, and domain-specific expertise.

Written specifically for machine learning engineers, AI researchers, and technical leaders, this practical handbook bypasses theoretical abstraction to deliver production-ready patterns, mathematical foundations, and real-world code structures for 2026 and beyond.

Inside this end-to-end engineering handbook, you will discover:
  • Parameter-Efficient Fine-Tuning (PEFT): Master the mathematics and implementation of LoRA, QLoRA, and weight updates on single A100 GPUs.
  • Advanced Alignment Techniques: Dive deep into Direct Preference Optimization (DPO), Reinforcement Learning from Human Feedback (RLHF), PPO, and Group Relative Policy Optimization (GRPO).
  • Domain Adaptation: Implement highly secure, compliant adaptations for complex legal, medical, and coding environments.
  • Production Deployment: Architect low-latency serving pipelines using vLLM, TensorRT-LLM, speculative decoding, and multi-LoRA routing.
  • MLOps & Governance: Build robust validation harnesses, evaluation pipelines, and continuous feedback loops.

Whether you are fine-tuning specialized medical assistants or scaling a code-generation platform, this guide provides the exact blueprints required to design, train, and deploy high-performing, aligned LLMs at scale. Transform your organization's AI strategy from standard API wrapper to proprietary powerhouse today!

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