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Description
vintage dress 1920s Vintage 1920s Cornflower Blue Tambour Beaded Silk DressLightweight silk chiffon in the most lovely shade of blue. Iconic flapper style with an open overlay, lower side panels, and original lining. Drop waist. Stunning blue and silver beading. The silk lining has a drawstring at the top. OVERVIEW MEASUREMENTS ETC. DETAILS: Label: none Fabric: Silk Circa: 1920s BEST FITS: L XL depending on how you prefer the fit (see measurements) CONDITION: Overall very good excellent. The dress shows light, normal wear
Lightweight silk chiffon in the most lovely shade of blue. Iconic flapper style with an open overlay, lower side panels, and original lining. Drop waist. Stunning blue and silver beading. The silk lining has a drawstring at the top.
-
DETAILS:
Label: none
Fabric: Silk
Circa: 1920s
BEST FITS: L/XL depending on how you prefer the fit (see measurements)
CONDITION: Overall very good - excellent. The dress shows light, normal wear and is extremely wearable (with care). There are just a few extremely minor issues to note. There are a few scattered, faint watermarks (the largest is pictured). There is some underarm discoloration (see photo), but this is mostly lost in the gathering of the drawstring. There also one small spot on the side (see photo). Although the dress was cleaned, we have not spot cleaned these specific areas. The dress presents beautifully and the few, small issues to not detract. Sold AS IS. -
Shoulders: approximately 16"
Bust: up to 42" with drawstring fully extended
Waist: up to 42"
Hips: up to 42"
Total length: 48" overall; 53" including the side panels
SIZING INFORMATION
- CARE:
Hand-wash; line dry or dry clean with a trusted cleaner experienced with older vintage. Contact us if you need more detailed care instructions.
SHIPPING:
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4.4 ★★★★★
Based on 14 reviews
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Product Reviews
★★★★★ 5
A wonderful primer for those discovering the amazing world of generative AI
Format: Paperback, Format: Paperback
Somewhere in the past year, ChatGPT has gone from "cool, interesting, amusing" to a massively valuable work assistant capable of writing Python scripts, analysing data, and doing lots, lots, more. The key to this? The rapid evolution of OpenAI's GPT models and making my first forays into prompt engineering.
If I thought I was getting good, though, this book took me reminded me that I'm just scratching the surface. Halfway through the first chapter I was already furiously scribbling notes in the margins for what I could do better with my prompt writing and by the end of the text I felt like I had gotten a very good grounding - not just in GPTs specifically but in the bigger picture of how these hugely powerful tools were trained and came to maturity.
I imagine that few will argue with my assertion that there is lots of hyperbole and "noise" in the AI space right now which, as ever, makes it hard to pick out the signal from the noise. Which is precisely why I sought out an O'Reilly title and I'm very glad that I did.
Thorough, excellent, and I hope that this edition will be the first of many. As this rapidly maturing field scales and matures I think that prompt engineering will be an essential discipline to master. Pick up this text to get a good foothold on things.
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Reviewed in the United States on August 3, 2024
★★★★★ 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
★★★★★ 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 25, 2024
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