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| Online-Ressource |
Verfasst von: | Doan, Ryan [VerfasserIn]  |
Titel: | Essential guide to LLMOps |
Titelzusatz: | implementing effective LLMOps strategies and tools from data to deployment |
Verf.angabe: | Ryan Doan |
Ausgabe: | 1st edition. |
Verlagsort: | Birmingham, UK |
Verlag: | Packt Publishing Ltd. |
Jahr: | 2024 |
Umfang: | 1 online resource (190 pages) |
Illustrationen: | illustrations |
Fussnoten: | Includes index |
ISBN: | 978-1-83588-750-9 |
Abstract: | The rapid advancements in large language models (LLMs) bring significant challenges in deployment, maintenance, and scalability. This Essential Guide to LLMOps provides practical solutions and strategies to overcome these challenges, ensuring seamless integration and the optimization of LLMs in real-world applications. This book takes you through the historical background, core concepts, and essential tools for data analysis, model development, deployment, maintenance, and governance. You’ll learn how to streamline workflows, enhance efficiency in LLMOps processes, employ LLMOps tools for precise model fine-tuning, and address the critical aspects of model review and governance. You’ll also get to grips with the practices and performance considerations that are necessary for the responsible development and deployment of LLMs. The book equips you with insights into model inference, scalability, and continuous improvement, and shows you how to implement these in real-world applications. By the end of this book, you’ll have learned the nuances of LLMOps, including effective deployment strategies, scalability solutions, and continuous improvement techniques, equipping you to stay ahead in the dynamic world of AI. |
URL: | Aggregator: https://learning.oreilly.com/library/view/-/9781835887509/?ar |
Datenträger: | Online-Ressource |
Sprache: | eng |
Sach-SW: | Traitement automatique des langues naturelles |
| Intelligence artificielle |
| artificial intelligence |
K10plus-PPN: | 1900847760 |
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Lokale URL UB: | Zum Volltext |
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| Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg |
| Bestellen/Vormerken für Benutzer des Klinikums Mannheim Eigene Kennung erforderlich |
Bibliothek/Idn: | UW / m4573896376 |
Lokale URL Inst.: | Zum Volltext |
978-1-83588-750-9
Essential guide to LLMOps / Doan, Ryan [VerfasserIn]; 2024 (Online-Ressource)
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