LLM engineer's handbook : (Record no. 141384)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02086nam a22002537a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260710164537.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 260710s2024 |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781836200079 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | PK-LaUMT |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.332 |
| Item number | LUS-L |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Iusztin, Paul |
| 245 10 - TITLE STATEMENT | |
| Title | LLM engineer's handbook : |
| Remainder of title | master the art of engineering large language models from concept to production / |
| Statement of responsibility, etc | Paul Iusztin and Maxime Labonne |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc | Birmingham : |
| Name of publisher, distributor, etc | Packt Publishing, |
| Date of publication, distribution, etc | 2024 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xxvi, 490 p. |
| 490 ## - SERIES STATEMENT | |
| Series statement | Expert insight |
| 500 ## - GENERAL NOTE | |
| General note | Index present |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | The field of Artificial Intelligence has undergone rapid advancements, and Large Language Models (LLMs) are at the forefront of this revolution. This LLM book provides practical insights into designing, training, and deploying LLMs in real-world scenarios by leveraging MLOps best practices. This comprehensive guide walks you through building an end-to-end LLM-powered technical content writer, by overcoming isolated Jupyter Notebooks and focusing on teaching 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, combined with detailed examples, helps you understand the implementation of MLOps components in your projects. The book also explores the cutting-edge advancements in the field, including inference optimization and real-time data processing, making it a vital resource for anyone looking to leverage LLMs in their projects. By the end of this book, you will be proficient in deploying robust large language models, leveraging them to solve practical problems, and maintaining low-latency and high-availability inference capabilities. Whether you are new to AI or an experienced practitioner, this book offers valuable insights and practical knowledge to enhance your expertise in LLMs |
| 546 ## - LANGUAGE NOTE | |
| Language note | Eng |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Machine learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Deep learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer software development |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Labonne, Maxime |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books |
| Withdrawn status | Lost status | Damaged status | Home library | Current library | Date acquired | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|
| UMT Main Campus | UMT Main Campus | 2026-07-10 | 006.332 LUS-L | 153327 | 2026-07-10 | 2026-07-10 | Books |