SKU: 33563861445

Size 11 Delica Set

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Size 11 Delica Set51 5. 2 gram Row 1 (left right) DB 0214 DB 0654 DB 0924 DB 0796 DB 0602 DB 0159 DB 0723 DB 2033 DB 0722 DB 0161 DB 1133 DB 0721 DB 0233 DB 2031 DB 160 DB 0733 DB 0238 ROW 2 (LEFT RIGHT) DB 0724 DB 0655 DB 0656 DB 2040 DB 2133 DB 0166 DB 2039 DB 0659 DB 0726 DB 0725 DB 0243 DB 0164 DB 0165 DB 0793 DB 0658 DB 1379 DB 0249 ROW 3 (LEFT RIGHT) DB 0660 DB 0661 DB 1345 DB 1340 DB 0246 DB 2036 DB 1371 DB 0236 DB 0794 DB 0042 DB 0041 DB 1211v DB 0202 DB 0200

Size 11 Delica Set
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SKU: 33563861445

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4.3 ★★★★★
Based on 2313 reviews
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S
Verified Purchase
Scott J. Pearson
Chelsea, US
★★★★★ 4
Understanding AI prompts as a science
Format: Audiobook
Prompt engineering is the art and science of finding the right words to generate the right responses from artificial intelligence (AI). It's becoming a skill in-demand in today's workplaces. It's also becoming an essential skill for life. To understand prompt engineering, you must understand how AI tools understand their inputs. This book explains that to you in many forms. It covers prompting as it intersects all the major AI disciplines, like general prompts (as in a ChatBot), fine-tuning, and retrieval-augmented generation (RAG). It also introduces how prompting intersects a couple of image-generation tools. As a scientist, I appreciate the theoretical approach to these practical matters. Too many people are hacks at AI these days, and any technical understanding can rapidly advance an individual's effectiveness. Prompt engineering is often made fun of as a "soft" topic, but as this book demonstrates, it intersects all the major AI areas. Presumably less garbage in means less garbage out. This book shows how you can make that take place. As typical for O'Reilly materials, this book appeals to people who desire an intermediate-to-advanced understanding of how AI works. It's not for the casual user. Anyone technical involved in professional knowledge generation using AI can benefit from understanding the dynamics "under the hood." It's a good, though perhaps not ground-breaking, textbook for those of us unable to take a class in the subject. Prompt engineering may be a soft topic to many, but books like this ground the field in the science that can make or break a digital or software product.
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Reviewed in the United States on December 13, 2025
J
Verified Purchase
Jason Bolton
San Leandro, US
★★★★★ 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
J
Verified Purchase
James Gianoglio
San Leandro, US
★★★★★ 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
M
Verified Purchase
Matt B
Cuba, US
★★★★★ 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
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SR
Dallas, US
★★★★★ 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

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