Isbn: 9798268504910 - mastering large language models: hands-on development, engineering, and production strategies (7 resultados)

Paperback. Condición: New.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

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Paperback. Condición: New.

Paperback. Condición: new. Paperback. Turn AI theory into practical, production-ready skills.Large Language Models (LLMs) are redefining how businesses operate-powering chatbots, intelligent assistants, and analytics pipelines across industries. Yet most resources stop at theory. This book bridges the gap between concept and implementation, guiding you through the entire lifecycle of an LLM: training, fine-tuning, evaluation, deployment, and scaling.Whether you're an engineer, data scientist, or AI enthusiast, you'll learn exactly how to build, optimize, and deploy real LLM-based systems using Python, Hugging Face, and modern frameworks.Inside You'll LearnCore LLM Foundations - Tokenization, embeddings, and Transformer architectures explained with working code.Fine-Tuning Strategies (Full, LoRA, Prompt Tuning) - Adapt models for specialized business tasks on limited hardware.Serving & Deployment - Turn your trained model into a FastAPI-powered API ready for production.Optimization & Evaluation - Boost performance using quantization, batching, and modern metrics (BLEU, ROUGE, Accuracy).Debugging & Governance - Handle hallucinations, drift, and ethical risks in real-world environments.Industry Use Cases - Finance, Marketing, HR, and IT workflows with full demos and case studies.Appendices with End-to-End Projects - Build your own customer service chatbot and multi-modal AI pipeline from scratch.What Makes This Book DifferentCode-first approach: Every concept is paired with runnable examples.Real-world case studies: Learn from finance, healthcare, and enterprise deployments.Practical, not theoretical: Build deployable models using accessible tools and cloud environments.Future-proof: Stay ahead of trends like parameter-efficient fine-tuning and AI governance.Who This Book Is ForAI Engineers & Data Scientists building production LLMsDevelopers integrating GPT-style APIs into productsTech leads seeking enterprise-ready AI solutionsStudents and researchers transitioning from NLP to applied LLMs This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condición: new. Paperback. Turn AI theory into practical, production-ready skills.Large Language Models (LLMs) are redefining how businesses operate-powering chatbots, intelligent assistants, and analytics pipelines across industries. Yet most resources stop at theory. This book bridges the gap between concept and implementation, guiding you through the entire lifecycle of an LLM: training, fine-tuning, evaluation, deployment, and scaling.Whether you're an engineer, data scientist, or AI enthusiast, you'll learn exactly how to build, optimize, and deploy real LLM-based systems using Python, Hugging Face, and modern frameworks.Inside You'll LearnCore LLM Foundations - Tokenization, embeddings, and Transformer architectures explained with working code.Fine-Tuning Strategies (Full, LoRA, Prompt Tuning) - Adapt models for specialized business tasks on limited hardware.Serving & Deployment - Turn your trained model into a FastAPI-powered API ready for production.Optimization & Evaluation - Boost performance using quantization, batching, and modern metrics (BLEU, ROUGE, Accuracy).Debugging & Governance - Handle hallucinations, drift, and ethical risks in real-world environments.Industry Use Cases - Finance, Marketing, HR, and IT workflows with full demos and case studies.Appendices with End-to-End Projects - Build your own customer service chatbot and multi-modal AI pipeline from scratch.What Makes This Book DifferentCode-first approach: Every concept is paired with runnable examples.Real-world case studies: Learn from finance, healthcare, and enterprise deployments.Practical, not theoretical: Build deployable models using accessible tools and cloud environments.Future-proof: Stay ahead of trends like parameter-efficient fine-tuning and AI governance.Who This Book Is ForAI Engineers & Data Scientists building production LLMsDevelopers integrating GPT-style APIs into productsTech leads seeking enterprise-ready AI solutionsStudents and researchers transitioning from NLP to applied LLMs This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…