• Medientyp: E-Book
  • Titel: Quick start guide to large language models : strategies and best practices for using ChatGPT, embeddings, fine-tuning, and multimodal AI
  • Beteiligte: Ozdemir, Sinan [Verfasser:in]
  • Erschienen: Hoboken, New Jersey: Addison-Wesley, [2025]
  • Erschienen in: Addison-Wesley data & analytics series
  • Ausgabe: Second edition.
  • Umfang: 1 online resource (384 pages); illustrations
  • Sprache: Englisch
  • Schlagwörter: Natural language processing (Computer science) ; Artificial intelligence ; Traitement automatique des langues naturelles ; Intelligence artificielle ; artificial intelligence
  • Entstehung:
  • Anmerkungen: Includes bibliographical references and index
  • Beschreibung: 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).