大規模言語モデル入門
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TWD 1152
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This book is an introductory book that explains both the theory and implementation of large-scale language models.
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What Stands Out
產品詳情
| Publisher | u6280u8853u8a55u8ad6u793e |
| Publication date | July 29, 2023 |
| Language | Japanese |
| Print length | 336 pages |
| ISBN-10 | 4297136333 |
| ISBN-13 | 978-4297136338 |
| Item Weight | 1 g |
| Dimensions | 9.06 x 7.17 x 0.63 inches (23 x 18.2 x 1.6 cm) |
Who Should Buy?
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AI Researchers
Ideal for researchers exploring advanced language models, providing insights into architecture, training, and applications.
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Students in AI
Beneficial for students of artificial intelligence who need foundational knowledge of language models for coursework and projects.
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Industry Professionals
Useful for professionals in tech fields looking to implement language models to enhance their products or services.
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Casual Readers
Not suitable for casual readers seeking light content, as it covers complex technical aspects of language models.
產品描述
大規模言語モデル入門
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山田 育矢 (Consultant Editor), 鈴木 正敏 Theoretical Computer Science Editorial Review
大規模言語モデル入門 is an insightful book published by 技術評論社 on July 29, 2023, exploring the complexities of large language models. With a print length of 336 pages, it offers a comprehensive overview in Japanese, making it accessible for native speakers and enthusiastic learners alike. The dimensions of the book, measuring 9.06 x 7.17 x 0.63 inches, suggest a convenient size for both reading and reference. Although there are no specific reviews to highlight, this publication aims to equip readers with the foundational knowledge needed in the rapidly evolving field of artificial intelligence.
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優點
- Comprehensive overview of large language models
- Published by a reputable publisher
- 336 pages of in-depth content
- Written in Japanese for local audience
- Compact size for easy reading
缺點
- Might require some prior knowledge in AI concepts
Product Price History
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TWD 1152
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特色和優勢
- Comprehensive guide to large-scale language models and their applications.
- Explains the theory behind natural language processing and neural networks.
- Utilizes Hugging Face's Python library for practical learning.
- Covers multilingual datasets, making it accessible for diverse users.
- Ideal for engineers, students, and researchers in tech fields.
- Offers insights on handling real-world language processing challenges.
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