SKU: 70333589458
maxi white and black dress

maxi white and black dress Miss Circle Women's Raelyn Black and White Business Casual Maxi Dress

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Description

maxi white and black dress Miss Circle Women's Raelyn Black and White Business Casual Maxi DressThe Raelyn Dress blends business casual sophistication with a vintage inspired charm, making it a timeless wardrobe essential. Designed in a classic black and white combo, this dress features a crisp white collar and an elegant halter neckline, exuding refined elegance. The high waist design and slim fit silhouette enhance your curves, while the bodycon cut ensures a sleek and polished look. A back slit allows for effortless movement, and the

The Raelyn Dress blends business casual sophistication with a vintage-inspired charm, making it a timeless wardrobe essential. Designed in a classic black and white combo, this dress features a crisp white collar and an elegant halter neckline, exuding refined elegance. The high-waist design and slim fit silhouette enhance your curves, while the bodycon cut ensures a sleek and polished look. A back slit allows for effortless movement, and the invisible zipper provides a seamless finish. Whether for office wear or an upscale event, the Raelyn Dress is the perfect balance of power and poise.

  • Materials: Woven Stretch Crepe
  • Length from underarm: Approx 53.1 inch / 135 cm
  • Stretch Factor: Mid Stretch
  • Clean: Dry-clean only
  • Model Is Wearing A Size XS (US-2)
  • Model Is 5'11'

Color may vary due to lighting on images. The product images (without model) are the closest to the true color of the product.

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SKU: 70333589458

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4.7 ★★★★★
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Verified Purchase
Daniel Rosehill
Dallas, US
★★★★★ 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 3, 2024
S
Verified Purchase
Scott J. Pearson
Pawtucket, 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
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 20, 2025
J
Verified Purchase
James Gianoglio
Natrona Heights, 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
Natrona Heights, 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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