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Fine Tuning Large Language Models

Adapting Foundation Models for Domain-Specific Intelligence and Performance Optimization

Language EnglishEnglish
Book Paperback
Book Fine Tuning Large Language Models Alex Ming
Libristo code: 51322935
Publishers Independently published, February 2026
Large language models provide powerful general capabilities, but real-world applications often requi... Full description
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Large language models provide powerful general capabilities, but real-world applications often require domain alignment, improved accuracy, and controlled behavior. Fine-Tuning Large Language Models provides a practical engineering roadmap for adapting foundation models to specialized use cases while maintaining stability, efficiency, and measurable performance.
This book covers the full fine-tuning lifecycle, including:

  1. Dataset curation and quality control
  2. Supervised fine-tuning (SFT) workflows
  3. Parameter-efficient tuning techniques
  4. Instruction tuning and conversational alignment
  5. Evaluation metrics and benchmarking strategies
  6. Overfitting mitigation and safety considerations
  7. Cost optimization and compute planning
Readers will gain structured insight into designing reproducible fine-tuning pipelines and assessing model performance in real environments. The focus remains on engineering discipline, experimentation rigor, and responsible model adaptation rather than hype or unrealistic performance claims.
This volume is ideal for machine learning engineers, applied researchers, and technical professionals seeking to move beyond prompt engineering toward controlled, measurable model customization.

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About the book

Full name Fine Tuning Large Language Models
Author Alex Ming
Language English
Binding Book - Paperback
Date of issue 2026
Number of pages 264
EAN 9798249390600
Libristo code 51322935
Publishers Independently published
Weight 465
Dimensions 178 x 254 x 14

Categories

Computing & Information Technology > Computer science > Artificial intelligence > Neural networks & fuzzy systems
Computing & Information Technology > Computer programming / software engineering > Programming & scripting languages: general
Computing & Information Technology > Databases > Data capture & analysis
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