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Building Private LLMs: A Guide to Fine-Tuning Open-Source Models for Business

by Thompson Carter
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Current price ₹2,093.00
Original price ₹2,315.00
Original price ₹2,315.00
Original price ₹2,315.00
(-10%)
₹2,093.00
Current price ₹2,093.00

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Book cover type: Paperback
  • ISBN13: 9798242460812
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Publication Date:
  • Pages: 342
  • Original Price: GBP 18.3
  • Language: English
  • Edition: N/A
  • Item Weight: 459 grams
  • BISAC Subject(s): Artificial Intelligence / Generative AI

Public AI models are powerful. Private models are strategic.

Enterprises increasingly rely on large language models-but sending sensitive data to public APIs is not always acceptable. Businesses need control, customization, and compliance. This book shows how to build and fine-tune private, open-source LLMs tailored to specific business needs.

Building Private LLMs is a practical guide to selecting, fine-tuning, evaluating, and deploying open-source language models in secure, business-ready environments.


What You'll Learn in This Book
  • When to use public APIs vs. private LLM deployments

  • Selecting the right open-source model for your use case

  • Fine-tuning strategies for domain-specific performance

  • Instruction tuning and parameter-efficient training methods

  • Dataset preparation and quality control

  • Evaluation frameworks for business reliability

  • Deployment options: on-prem, cloud, and hybrid

  • Governance, compliance, and data privacy considerations

The focus is on practical implementation for real organizations, not research experiments.


Who This Book Is For

This guide is ideal for:

  • AI engineers and ML practitioners

  • Data scientists building internal AI tools

  • Enterprise architects

  • Technical founders building AI-first companies

  • Organizations requiring data control and compliance

Familiarity with Python and machine learning concepts is recommended.


Why Private LLMs Matter for Business

Private deployments enable organizations to:

  • Protect sensitive data

  • Customize models for domain expertise

  • Reduce long-term API dependency

  • Optimize cost at scale

  • Maintain regulatory compliance

This book teaches how to treat LLMs as infrastructure assets, not external black boxes.

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