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 Online-Ressource
Verfasst von:Ozdemir, Sinan [VerfasserIn]   i
Titel:Quick start guide to large language models
Titelzusatz:strategies and best practices for using ChatGPT, embeddings, fine-tuning, and multimodal AI
Verf.angabe:Sinan Ozdemir
Ausgabe:Second edition.
Verlagsort:Hoboken, New Jersey
Verlag:Addison-Wesley
E-Jahr:2025
Jahr:[2025]
Umfang:1 online resource (384 pages)
Illustrationen:illustrations
Gesamttitel/Reihe:Addison-Wesley data & analytics series
Fussnoten:Includes bibliographical references and index
Abstract:Large Language Models (LLMs) like Llama 3, Claude 3, and the GPT family are demonstrating breathtaking capabilities, but their size and complexity have deterred many practitioners from applying them. In Quick Start Guide to Large Language Models, Second Edition, pioneering data scientist and AI entrepreneur Sinan Ozdemir clears away those obstacles and provides a guide to working with, integrating, and deploying LLMs to solve practical problems. Ozdemir brings together all you need to get started, even if you have no direct experience with LLMs: step-by-step instructions, best practices, real-world case studies, and hands-on exercises. Along the way, he shares insights into LLMs' inner workings to help you optimize model choice, data formats, prompting, fine-tuning, performance, and much more. The resources on the companion website include sample datasets and up-to-date code for working with open- and closed-source LLMs such as those from OpenAI (GPT-4 and GPT-3.5), Google (BERT, T5, and Gemini), X (Grok), Anthropic (the Claude family), Cohere (the Command family), and Meta (BART and the LLaMA family).
URL:Aggregator: https://learning.oreilly.com/library/view/-/9780135346570/?ar
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:Traitement automatique des langues naturelles
 Intelligence artificielle
 artificial intelligence
K10plus-PPN:1903889685
 
 
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