| |  Online-Ressource |
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| Titel: | LLMs under the hood |
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| Titelzusatz: | building models for your unique use cases |
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| Mitwirkende: | Labonne, Maxime [MitwirkendeR]  |
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| | Rothman, Denis [MitwirkendeR] |
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| | Aryan, Abi [MitwirkendeR] |
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| Institutionen: | Packt Publishing, [Verlag] |
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| Ausgabe: | [First edition]. |
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| Verlagsort: | [Place of publication not identified] |
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| Verlag: | Packt Publishing |
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| Jahr: | 2024 |
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| Umfang: | 1 online resource (1 video file (4 hr., 2 min.)) |
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| Illustrationen: | sound, color. |
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| Fussnoten: | Online resource; title from title details screen (O'Reilly, viewed February 8, 2024) |
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| ISBN: | 978-1-83588-354-9 |
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| | 1-83588-354-0 |
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| Abstract: | This in-depth masterclass provides end-to-end coverage of developing enterprise-grade LLMs tailored to your unique use cases. Led by experts Maxime Labonne, Dennis Rothman, and Abi Aryan, this video delivers the advanced skills needed to architect performant LLMs that deliver real business impact. You'll learn how to make crucial architecture decisions, select optimal model types, configure hyperparameters, and curate quality training data. Discover professional techniques for pre-training, iterative fine-tuning, and rigorous model evaluation. The instructors reveal insider strategies to productionize your LLMs smoothly, monitor them proactively, and maintain optimal performance post-deployment. Following a structured curriculum spanning the complete LLM lifecycle, this masterclass empowers you with hands-on skills to build, refine, and deploy large language models with confidence. Turbocharge your generative AI initiatives and get the practical knowledge needed to create LLMs that solve complex challenges for your organization. What you will learn How to select the right LLM architecture for your use case Approaches for sourcing, cleaning, and labeling quality training data Pre-training methods and hyperparameter optimization Advanced fine-tuning techniques to boost performance Ways to thoroughly evaluate LLMs before deployment Best practices for monitoring, updating, and maintaining production LLMs Audience Data scientists, machine learning engineers, and AI developers seeking an in-depth understanding of large language model (LLM) development. This masterclass is designed for professionals aiming to build, optimize, and deploy enterprise-grade LLMs tailored to specific use cases, with a focus on practical skills and real business impact. About the Authors Maxime Labonne: Sr. Machine Learning Scientist, JPMorgan. Denis Rothman: Expert in AI Transformers including ChatGPT/GPT-4, Bestselling Author. Abi Aryan: ML Engineer and Author. |
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| URL: | Aggregator: https://learning.oreilly.com/library/view/-/9781835883549/?ar |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Sach-SW: | Traitement automatique des langues naturelles |
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| | Intelligence artificielle |
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| | artificial intelligence |
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| | Instructional films |
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| | Nonfiction films |
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| | Internet videos |
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| | Films de formation |
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| | Films autres que de fiction |
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| | Vidéos sur Internet |
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| K10plus-PPN: | 1881694399 |
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| Lokale URL UB: |  Zum Volltext |
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| | Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg |
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| |  Bestellen/Vormerken für Benutzer des Klinikums Mannheim
Eigene Kennung erforderlich |
| Bibliothek/Idn: | UW / m4491975221 |
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| Lokale URL Inst.: | Zum Volltext |
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