Stella biderman (7 Ergebnisse)
- Softcover
Anbieter: BooksRun, Philadelphia, PA, USABooksRun
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EUR 23,72
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Paperback. Zustand: Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
- Softcover
Anbieter: World of Books (was SecondSale), Montgomery, IL, USAWorld of Books (was SecondSale)
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Zustand: Good. Item in good condition and has highlighting/writing on text. Used texts may not contain supplemental items such as CDs, info-trac etc.
- Softcover
Anbieter: Majestic Books, Hounslow, Vereinigtes KönigreichMajestic Books
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EUR 56,74
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Zustand: New.
- Softcover
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USARomtrade Corp.
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EUR 65,58
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Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
- Softcover
Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books
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EUR 64,02
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Paperback. Zustand: Brand New. 176 pages. 9.00x7.25x0.50 inches. In Stock.
- Softcover
Anbieter: Studibuch, Stuttgart, DeutschlandStudibuch
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EUR 38,96
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paperback. Zustand: Sehr gut. 200 Seiten; 9781633437081.2 Gewicht in Gramm: 500.
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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EUR 58,18
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Taschenbuch. Zustand: Neu. Neuware - Learn how large language models like GPT and Gemini work under the hood in plain English.How Large Language Models Work translates years of expert research on Large Language Models into a readable, focused introduction to working with these amazing systems. It explains clearly how LLMs functi…on, introduces the optimization techniques to fine-tune them, and shows how to create pipelines and processes to ensure your AI applications are efficient and error-free. In How Large Language Models Work you will learn how to: Test and evaluate LLMs Use human feedback, supervised fine-tuning, and Retrieval Augmented Generation (RAG) Reducing the risk of bad outputs, high-stakes errors, and automation bias Human-computer interaction systems Combine LLMs with traditional ML How Large Language Models Work is authored by top machine learning researchers at Booz Allen Hamilton, including researcher Stella Biderman, Director of AI/ML Research Drew Farris, and Director of Emerging AI Edward Raff. They lay out how LLM and GPT technology works in plain language that's accessible and engaging for all. About the Technology Large Language Models put the "I" in "AI." By connecting words, concepts, and patterns from billions of documents, LLMs are able to generate the human-like responses we've come to expect from tools like ChatGPT, Claude, and Deep-Seek. In this informative and entertaining book, the world's best machine learning researchers from Booz Allen Hamilton explore foundational concepts of LLMs, their opportunities and limitations, and the best practices for incorporating AI into your organizations and applications. About the Book How Large Language Models Work takes you inside an LLM, showing step-by-step how a natural language prompt becomes a clear, readable text completion. Written in plain language, you'll learn how LLMs are created, why they make errors, and how you can design reliable AI solutions. Along the way, you'll learn how LLMs "think," how to design LLM-powered applications like agents and Q&A systems, and how to navigate the ethical, legal, and security issues. What's Inside Customize LLMs for specific applications Reduce the risk of bad outputs and bias Dispel myths about LLMs Go beyond language processing About the Readers No knowledge of ML or AI systems is required. About the Author Edward Raff, Drew Farris and Stella Biderman are the Director of Emerging AI, Director of AI/ML Research, and machine learning researcher at Booz Allen Hamilton. Table of Contents 1 Big picture: What are LLMs 2 Tokenizers: How large language models see the world 3 Transformers: How inputs become outputs 4 How LLMs learn 5 How do we constrain the behavior of LLMs 6 Beyond natural language processing 7 Misconceptions, limits, and eminent abilities of LLMs 8 Designing solutions with large language models 9 Ethics of building and using LLMs Get a free Elektronisches Buch (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.
