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LLM Engineer's Handbook: Master the - Taschenbuch, von Iusztin Paul; Labonne - gut-
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eBay-Artikelnr.:406172394986
Artikelmerkmale
- Artikelzustand
- Book Title
- LLM Engineer's Handbook: Master the art of engineering large lang
- ISBN
- 9781836200079
Über dieses Produkt
Product Identifiers
Publisher
Packt Publishing, The Limited
ISBN-10
1836200072
ISBN-13
9781836200079
eBay Product ID (ePID)
14072432522
Product Key Features
Publication Name
LLM Engineer's Handbook : Master the Art of Engineering Large Language Models from Concept to Production
Language
English
Subject
Intelligence (Ai) & Semantics, Natural Language Processing, Neural Networks, General
Publication Year
2024
Type
Textbook
Subject Area
Computers, Science
Format
Trade Paperback
Dimensions
Item Length
92.5 in
Item Width
75 in
Additional Product Features
Intended Audience
Trade
Dewey Edition
23
Dewey Decimal
006.3
Synopsis
Step into the world of LLMs with this practical guide that takes you from the fundamentals to deploying advanced applications using LLMOps best practices Book Description Artificial 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 learn - Implement robust data pipelines and manage LLM training cycles - Create your own LLM and refine it with the help of hands-on examples - Get started with LLMOps by diving into core MLOps principles such as orchestrators and prompt monitoring - Perform supervised fine-tuning and LLM evaluation - Deploy end-to-end LLM solutions using AWS and other tools - Design scalable and modularLLM systems - Learn about RAG applications by building a feature and inference pipeline 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 on implementing LLMs in real-world scenarios. Table of Contents - Undersstanding the LLM Twin Concept and Architecture - Tooling and Installation - Data Engineering - RAG Feature Pipeline - Supervised Fine-tuning - Fine-tuning with Preference Alignment - Evaluating LLMs - Inference Optimization - RAG Inference Pipeline - Inference Pipeline Deployment - MLOps and LLMOps - Appendix: MLOps Principles, Step into the world of LLMs with this practical guide that takes you from the fundamentals to deploying advanced applications using LLMOps best practices Key Features Build and refine LLMs step by step, covering data preparation, RAG, and fine-tuning Learn essential skills for deploying and monitoring LLMs, ensuring optimal performance in production Utilize preference alignment, evaluation, and inference optimization to enhance performance and adaptability of your LLM applications Book Description Artificial 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 learn Implement robust data pipelines and manage LLM training cycles Create your own LLM and refine it with the help of hands-on examples Get started with LLMOps by diving into core MLOps principles such as orchestrators and prompt monitoring Perform supervised fine-tuning and LLM evaluation Deploy end-to-end LLM solutions using AWS and other tools Design scalable and modularLLM systems Learn about RAG applications by building a feature and inference pipeline 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 on implementing LLMs in real-world scenarios ]]>
LC Classification Number
Q335.I9 2024
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- 6***4 (84)- Bewertung vom Käufer.Letzter MonatBestätigter KaufThe best book out there about AI
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- c***e (34)- Bewertung vom Käufer.Letzter MonatBestätigter KaufThe textbook was better than described. It looks like brand new! The price was appropriate for the type of textbook that it is. The appearance and quality of the textbook was impeccable. The shipping took about 2 weeks to arrive, but the textbook was well worth the wait. Seller packaged my textbook beautifully which ensured that it arrived unharmed and in perfect condition. Excellent seller! I would purchase more items from this seller in the future!
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- 6***4 (84)- Bewertung vom Käufer.Letzter MonatBestätigter KaufThe best book out there about AI
- 7***j (849)- Bewertung vom Käufer.Letzte 6 MonateBestätigter KaufI recently purchased an item from this eBay seller, and I couldn't be happier with the experience. From the prompt communication to the fast shipping, everything was handled with utmost professionalism. The item arrived exactly as described and was well-packaged to ensure its safety during transit. The seller was courteous and responsive, making the entire transaction smooth and hassle-free. I highly recommend this seller to anyone looking for quality products and excellent service.
- c***m (443)- Bewertung vom Käufer.Letzte 6 MonateBestätigter KaufWOW!; I cannot believe this 4 Days to Hawaii! ; AAA+++; Excellent Service; Great Pricing; Fast Delivery-Faster Than Expected to Hawaii!; Shipped 04/19, Sat, Received 04/24 Thur to Hawaii using free shipping; USPS Ground Mail, Paperback Book in Good Condition--Better Than Described ; TLC Packaging; Excellent Seller Communication, Sends updates . Highly Recommended!, Thank you very much!The Great Crash, 1929 - Paperback, by J K Galbraith - Acceptable (Nr. 125958575357)
- c***e (34)- Bewertung vom Käufer.Letzter MonatBestätigter KaufThe textbook was better than described. It looks like brand new! The price was appropriate for the type of textbook that it is. The appearance and quality of the textbook was impeccable. The shipping took about 2 weeks to arrive, but the textbook was well worth the wait. Seller packaged my textbook beautifully which ensured that it arrived unharmed and in perfect condition. Excellent seller! I would purchase more items from this seller in the future!