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LLM Engineer's Handbook: Master the art of engineering large language models from concept to production

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Livraison entre le Jeudi 10 septembre 2026 et le Vendredi 11 septembre 2026

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Marque : GENERIC
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Step into the world of LLMs with this practical guide that takes you from the fundamentals to deploying advanced applications using LLMOps best practicesGet With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader FreeKey FeaturesBuild and refine LLMs step by step, covering data preparation, RAG, and fine-tuningLearn essential skills for deployi...

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Description produit

Marque
GENERIC
Titre
LLM Engineer's Handbook: Master the art of engineering large language models from concept to production
Éditeur
Packt Publishing
Type de produit
paperback
Présentation du livre
paperback
Date de sortie
10/22/2024 12:00:00 AM
Langue d'origine
English
ISBN
1836200072
Nombre de pages
522 pages
Langue
English
Résumé
Step into the world of LLMs with this practical guide that takes you from the fundamentals to deploying advanced applications using LLMOps best practicesGet With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader FreeKey FeaturesBuild and refine LLMs step by step, covering data preparation, RAG, and fine-tuningLearn essential skills for deploying and monitoring LLMs, ensuring optimal performance in productionUtilize preference alignment, evaluation, and inference optimization to enhance performance and adaptability of your LLM applicationsBook DescriptionArtificial intelligence has undergone rapid advancements, and Large Language Models (LLMs) are at the forefront of this revolution. This LLM book offers insights into designing, training, and deploying LLMs in real-world scenarios by leveraging MLOps best practices. The guide walks you through building an LLM-powered twin that’s cost-effective, scalable, and modular. It moves beyond isolated Jupyter notebooks, focusing on how to build production-grade end-to-end LLM systems.Throughout this book, you will learn data engineering, supervised fine-tuning, and deployment. The hands-on approach to building the LLM Twin use case will help you implement MLOps components in your own projects. You will also explore cutting-edge advancements in the field, including inference optimization, preference alignment, and real-time data processing, making this a vital resource for those looking to apply LLMs in their projects.By the end of this book, you will be proficient in deploying LLMs that solve practical problems while maintaining low-latency and high-availability inference capabilities. Whether you are new to artificial intelligence or an experienced practitioner, this book delivers guidance and practical techniques that will deepen your understanding of LLMs and sharpen your ability to implement them effectively.What you will learnImplement robust data pipelines and manage LLM training cyclesCreate your own LLM and refine
Auteur
Paul Iusztin, Maxime Labonne
Date de parution
10/22/2024 12:00:00 AM