{ "item_title" : "Building Private LLMs", "item_author" : [" Thompson Carter "], "item_description" : "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 BookWhen to use public APIs vs. private LLM deploymentsSelecting the right open-source model for your use caseFine-tuning strategies for domain-specific performanceInstruction tuning and parameter-efficient training methodsDataset preparation and quality controlEvaluation frameworks for business reliabilityDeployment options: on-prem, cloud, and hybridGovernance, compliance, and data privacy considerationsThe focus is on practical implementation for real organizations, not research experiments.Who This Book Is ForThis guide is ideal for: AI engineers and ML practitionersData scientists building internal AI toolsEnterprise architectsTechnical founders building AI-first companiesOrganizations requiring data control and complianceFamiliarity with Python and machine learning concepts is recommended.Why Private LLMs Matter for BusinessPrivate deployments enable organizations to: Protect sensitive dataCustomize models for domain expertiseReduce long-term API dependencyOptimize cost at scaleMaintain regulatory complianceThis book teaches how to treat LLMs as infrastructure assets, not external black boxes.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/9/79/824/246/9798242460812_b.jpg", "price_data" : { "retail_price" : "24.99", "online_price" : "24.99", "our_price" : "24.99", "club_price" : "24.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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