LLM Engineer's Handbook (Record no. 70822)

MARC details
000 -LEADER
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005 - DATE AND TIME OF LATEST TRANSACTION
control field 20261003112635.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781836200079
028 ## - DISTRIBUTOR NAME
Distributor Name Technical Bureau India Pvt. Ltd.
Distributor address 4794/23, 1st Floor, Ansari Road, Daryaganj, New Delhi
Bill Number TB2198
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.35 LIS
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Iusztin, Paul.
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name ; Labonne, Maxime.
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name ; Chaumond, Julien.
245 ## - 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.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc , Birmingham
Name of publisher, distributor, etc : Packet Publishing House
Date of publication, distribution, etc , 2024.
300 ## - PHYSICAL DESCRIPTION
Extent xxvi, 490p.
Dimensions : 24cm.
365 ## - TRADE PRICE
Price amount 4499
520 ## - SUMMARY, ETC.
Summary, etc 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.<br/><br/>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.<br/><br/>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.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Large Language Models
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element LLMs
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Paul Iusztin.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification   Not For Loan SNU LIBRARY SNU LIBRARY 03/10/2026 Technical Bureau India Pvt. Ltd. 4499.00   006.35 LIS 31797 03/10/2026 03/10/2026 Books
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