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Llm Engineers Handbook Master The Art Of Engineering Large Language Models From Concept To Production 1st Edition Paul Iusztin

  • SKU: BELL-67742064
Llm Engineers Handbook Master The Art Of Engineering Large Language Models From Concept To Production 1st Edition Paul Iusztin
$ 31.00 $ 45.00 (-31%)

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Llm Engineers Handbook Master The Art Of Engineering Large Language Models From Concept To Production 1st Edition Paul Iusztin instant download after payment.

Publisher: Packt Publishing
File Extension: PDF
File size: 19.65 MB
Pages: 523
Author: Paul Iusztin, Maxime Labonne
Language: English
Year: 2024
Edition: 1

Product desciption

Llm Engineers Handbook Master The Art Of Engineering Large Language Models From Concept To Production 1st Edition Paul Iusztin by Paul Iusztin, Maxime Labonne instant download after payment.

Step into the world of LLMs with this practical guide that takes you from the fundamentals to deploying advanced applications using LLMOps best practices

“This book is instrumental in making sure that as many people as possible can not only use LLMs but also adapt them, fine-tune them, quantize them, and make them efficient enough to deploy in the real world.”- Julien Chaumond, CTO and Co-founder, Hugging Face

This LLM book provides practical 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.

What you will learn
• Implement robust data pipelines and manage LLM training cycles
• Create your own LLM and refine with the help of hands-on examples
• Get started with LLMOps by diving into core MLOps principles like IaC
• Perform supervised fine-tuning and LLM evaluation
• Deploy end-to-end LLM solutions using AWS and other tools
• Explore continuous training, monitoring, and logic automation
• Learn about RAG ingestion as well as inference and feature pipelines

Who this book is for
This book is for AI engineers, NLP professionals, and LLM engineers looking to deepen their understanding of LLMs. Basic knowledge of LLMs and the Gen AI landscape, Python and AWS is recommended. Whether you are new to AI or looking to enhance your skills, this book provides comprehensive guidance

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