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portada Fine Tuning Large Language Models for Domain Specific Applications. Training Data Preparation, Adaptation Techniques, and Performance Optimization for LLM Systems
Type
Physical Book
Publisher
Author
Year
2026
Language
English
Pages
352
Format
Paperback
Dimensions
25.4x17.8x1.8 cm
ISBN13
9798251249903

Fine Tuning Large Language Models for Domain Specific Applications. Training Data Preparation, Adaptation Techniques, and Performance Optimization for LLM Systems

Marcus Linford (Author) · Independently published · Paperback

Fine Tuning Large Language Models for Domain Specific Applications. Training Data Preparation, Adaptation Techniques, and Performance Optimization for LLM Systems - Marcus Linford

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Synopsis "Fine Tuning Large Language Models for Domain Specific Applications. Training Data Preparation, Adaptation Techniques, and Performance Optimization for LLM Systems"

Large language models provide powerful general-purpose capabilities, but many real-world applications require models that understand specialized terminology, structured tasks, or domain-specific information. Fine-tuning enables developers to adapt pre-trained models so they perform more effectively within targeted environments.
Fine-Tuning Large Language Models for Domain-Specific Applications examines the technical processes used to customize language models through structured training methods and dataset preparation strategies.
The book explains how developers can refine model behavior, improve response quality, and adapt large language models to specialized use cases while maintaining responsible and efficient development practices.
Topics explored throughout this book include:Foundations of language model training and adaptationPreparing datasets for supervised fine-tuning workflowsStructuring prompts and instruction-based training dataEvaluation methods for measuring model performanceStrategies for improving accuracy and consistency in outputsDeployment considerations for fine-tuned models in applicationsBy providing a clear explanation of the fine-tuning process and its practical implementation, this book helps developers move from general-purpose AI models toward more specialized and effective intelligent systems.

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