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Katsumi Okuda (Author)
 Original text before translation
奥田 勝己 (著)
(185260)
JAN:9784798185262
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(185260)
JAN:9784798185262
Wholesale Price: Members Only
1 pc /set
In Stock
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| Shipping Date |
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About 1 week
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| Dimensions |
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Format:B5
Number of pages:376 |
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Country of manufacture: Japan
Material / component: Format:Book (paper)
Year of manufacture: 2025
Product tag: None
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Description
| A must-have for anyone who wants to learn LLM systematically, from the basics to an introduction to software development This book is an introduction to software development using the Large Language Model (LLM), allowing you to systematically learn its structure and development techniques in a single volume. LLM is changing the way of software development as an indispensable technology in the era of generative AI, and is evolving as an [intelligent engine] that can be applied in all areas. The possibilities of LLM will be further expanded by implementing RAGs using frameworks such as LangChain and building multi-agent systems. To master LLM, it is essential to acquire basic knowledge of the Transformer mechanism, the learning process, and prompt engineering. This book carefully explains these techniques and describes the open source Llama 3 to provide a white box perspective on practical LLM. The book also provides a wealth of Python code examples to help students acquire practical skills, and introduces the use of representative APIs (OpenAI API, Anthropic API, and Gemini API). The course is structured so that participants can acquire skills that can be applied through development examples using LangChain and LangGraph. Through this book, you will learn how multimodal LLM works, how to develop applications using LangChain and LangGraph, and how to deploy multimodal RAGs and multi-agent systems. [Skills and prerequisites for this book] *Basic Python syntax *How to build a Python environment [Table of Contents] Chapter 1 Transformer Chapter 2 Learning Chapter 3 Prompt Engineering Chapter 4 Language Model API Chapter 5 LLM Framework -LangChain Chapter 6 Multi-Agent Framework -LangGraph Chapter 7 Applications Appendix [Author's Profile] Katsumi Okuda Chief Researcher, Advanced Technology Research Institute, Mitsubishi Electric Corporation. D. (Information Science and Engineering), Graduate School of Information Science and Engineering, The University of Tokyo. D. in Information Science and Engineering, he was a visiting researcher at the Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT) for two years from March 2023, where he was engaged in research on code optimization and programming language technology using LLMs (large-scale language models). In the corporate world, he has worked for many years on research and development of programming language technology, compilers, and embedded systems. The results of his work have been applied to the development of actual products and systems, such as factory automation (FA) systems and advanced space systems. |
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| EMS | From Dec.2nd 2025 to Dec.5th 2025 |
| Pantos Express | From Dec.4th 2025 to Dec.9th 2025 |
| DHL | From Dec.2nd 2025 to Dec.4th 2025 |
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Other items from this category:
This book is an introduction to software development using the Large Language Model (LLM), allowing you to systematically learn its structure and development techniques in a single volume.
LLM is changing the way of software development as an indispensable technology in the era of generative AI, and is evolving as an [intelligent engine] that can be applied in all areas. The possibilities of LLM will be further expanded by implementing RAGs using frameworks such as LangChain and building multi-agent systems.
To master LLM, it is essential to acquire basic knowledge of the Transformer mechanism, the learning process, and prompt engineering. This book carefully explains these techniques and describes the open source Llama 3 to provide a white box perspective on practical LLM.
The book also provides a wealth of Python code examples to help students acquire practical skills, and introduces the use of representative APIs (OpenAI API, Anthropic API, and Gemini API). The course is structured so that participants can acquire skills that can be applied through development examples using LangChain and LangGraph.
Through this book, you will learn how multimodal LLM works, how to develop applications using LangChain and LangGraph, and how to deploy multimodal RAGs and multi-agent systems.
[Skills and prerequisites for this book]
*Basic Python syntax
*How to build a Python environment
[Table of Contents]
Chapter 1 Transformer
Chapter 2 Learning
Chapter 3 Prompt Engineering
Chapter 4 Language Model API
Chapter 5 LLM Framework -LangChain
Chapter 6 Multi-Agent Framework -LangGraph
Chapter 7 Applications
Appendix
[Author's Profile] Katsumi Okuda
Chief Researcher, Advanced Technology Research Institute, Mitsubishi Electric Corporation. D. (Information Science and Engineering), Graduate School of Information Science and Engineering, The University of Tokyo. D. in Information Science and Engineering, he was a visiting researcher at the Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT) for two years from March 2023, where he was engaged in research on code optimization and programming language technology using LLMs (large-scale language models). In the corporate world, he has worked for many years on research and development of programming language technology, compilers, and embedded systems. The results of his work have been applied to the development of actual products and systems, such as factory automation (FA) systems and advanced space systems.