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Description
MARK.S MS0006 ZIP PARKER SIIKI-MUD-DYESIIKI MUD DYE 34 4 8 2: 86cm 66cm 78cm 3: 88cm 68cm 80cm : 174cm 52kg 2 Cotton 100% Japan MS0006 VR26SMS015
〈SIIKI-MUD-DYE 染色工程〉椎木をチップ状にし、煮出した後に3〜4日寝かせて染料を抽出します。
その染料で染色を行ったのち、泥田での染め工程を重ねることで色を定着させていきます。
この一連の工程を、合計4回繰り返すことで、深みのある色合いを生み出しています。
椎木は奄美大島では「スダジイ」と呼ばれ、島の森林の約8割に自生する、生態系の中心的な植物です。
工房では、染色のたびに近隣の山から必要な分だけを少しずつ切り出し、自然環境に配慮しながら使用しています。
サイズ
2: 裄丈 86cm 身幅 66cm 着丈 78cm
3: 裄丈 88cm 身幅 68cm 着丈 80cm
着用モデル体型: 174cm 52kg / 着用サイズ 2
素材
Cotton 100%
生産国
Japan
型番
MS0006
問合せ番号
VR26SMS015
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4.7 ★★★★★
Based on 352 reviews
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Product Reviews
★★★★★ 5
Great book
Format: Paperback
Great book! It is helpful as I work towards my Masters of Science in Applied Artificial Intelligence
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Reviewed in the United States on December 20, 2025
★★★★★ 5
Comprehensive Guide with Practical Insights
Format: Paperback
This is a solid book for understanding the art and science of working with LLMs and other generative AI models. I always struggled with getting the output I was looking for, and wasn't sure how best to "ask" the models for what I wanted. This book did a great job of laying out the strategies and practical guidance to craft the prompts. There were a lot of tips and tricks, but the overall understanding and framework around prompt engineering has been super useful.
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Reviewed in the United States on June 25, 2024
★★★★★ 5
A must read!
Format: Paperback
Hands down, the best book on prompt engineering and implementing LLMs. Really enjoyed Michael and James deep dive. Whether you're technical or not, this book is foundational to a deeper understanding in how to properly explore and implement LLMs.
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Reviewed in the United States on June 25, 2024
★★★★★ 4
Helpful for GPT/LangChain framework
Format: Paperback
I applaud the authors for putting forth a comprehensive introduction in a rapidly evolving space. I absorbed a lot, helpful as I was developing a prototype — using open source methods.
And that’s where I was disappointed. The LLM and examples are highly adapted to OpenAI’s GPT-x and the bulky LangChain framework, something not obvious until you dig in to the book. Sure, this may be where newbie demand was when the authors began writing. But as the open source models and OpenAI alternatives gain speed (e.g. Llama 3.1, Groq, etc.) this book may quickly need an updated and expanded version to stay relevant.
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Reviewed in the United States on August 7, 2024
★★★★★ 3
Good concepts, but uneven depth
Format: Paperback
Some helpful prompt frameworks, but parts felt repetitive and a few sections stayed too high-level for advanced users. Beginners will likely benefit more than experienced practitioners. If you’re new to prompt engineering it’s a decent starting point; if you’re already building structured prompts daily, it may feel light.
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Reviewed in the United States on January 17, 2026