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Description
SONGMICS 18 Pack Foldable Stackable Shoe Boxes Max AU Size 11 Black TransparentSONGMICS 18 Pack Foldable Stackable Shoe Boxes Max AU Size 11 Black Transparent LSP18SBKV1 OVERVIEW Do Away with Shoe Piles: Are you someone who shoves all your shoes into the closet in a big pile? Dont let your old habits get the best of you, keep them shapely, clean, and dry with this pack of 18 shoe boxes until you wear them for the next occasion or season. Kick Mess to the Curb: If your home is slowly but surely becoming a mess of shoes, why not
SONGMICS 18 Pack Foldable Stackable Shoe Boxes Max AU Size 11 Black TransparentLSP18SBKV1
OVERVIEW
Do Away with Shoe Piles: Are you someone who shoves all your shoes into the closet in a big pile? Don’t let your old habits get the best of you, keep them shapely, clean, and dry with this pack of 18 shoe boxes until you wear them for the next occasion or season.
-
Kick Mess to the Curb:
If your home is slowly but surely becoming a mess of shoes, why not organise them in this pack of 18 classic shoe boxes with transparent body and front door? See your whole collection in order -
Keep It Clear:
You don’t have to take out and dig through your shoe boxes to look for your commuting shoes every morning, the clear body with transparent front door gives you a glimpse inside your tower of kicks with a grab-and-dash ease -
A Snap to Set Up:
Simply slot the front, back, and body together and you’ll have these shoe organisers with an inner size of 31.2 x 22.5 x 13.5 cm for max. UK size 11; each pair of sneakers, heels, or flats will have a place of its own - Stack ’Em Up: If you want to store the boxes in an organised way, the corresponding slot design on the top and bottom makes stacking them a snap; ventilation holes let your shoes breathe
- What You Get: Pack of 18 transparent shoe boxes with clear front door, stackable and foldable design, ventilation holes. Say goodbye to scattered shoes everywhere and put your shoes in order now!
- Color: Transparent, Black
- Material: PP (Polypropylene) Plastic Body, PP (Polypropylene) Front Door, ABS Plastic Frame
- Internal Size of Single Box: 30 x 22.5 x 13.5 cm
- Product Weight: 5.3 kg
- 18 x Shoe Box
- 1 x Instructions
- For product assembly, please refer to the steps in the instructions and the assembly video. Do not disassemble the product by force.
- Please measure your shoe length and then check the corresponding shoe box size before your purchase.
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- Free Standard Shipping on $100+ Orders to the USA.
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Exchange/Return Notes
- We offer a 30-day return/exchange service after receiving.
- Final sale items are not eligible for returns or exchanges.
- To process your return/exchange, please contact us at [email protected]
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4.5 ★★★★★
Based on 16 reviews
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Product Reviews
★★★★★ 5
a comprehensive guide at the intersection of generative AI and cybersecurity
Format: Kindle
This book blends deep theoretical foundations with practical frameworks and forward-looking strategies. From adversarial risk models to actionable guidance using OWASP Top 10 for LLMs and the NIST AI RMF, it offers both technical depth and operational clarity.
What makes it stand out is its balance of academic rigor and real-world CISO insights, providing a holistic perspective on securing GenAI systems. While it leans enterprise-focused, the content remains accessible to security engineers, risk managers, and policy leaders alike.
Generative AI Security is a timely and essential read for anyone working to deploy GenAI responsibly—building systems with both power and integrity in today’s fast-evolving threat landscape.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 2, 2025
★★★★★ 1
Light on substance and heavy on flaws
Format: Paperback
The book has a great list of topics, but fails to provide much substance any of them.
Most of the provided code is just comments that avoid the actual crux of the issues being discussed. (e.g. #implement the logic to validate XYZ - while the whole point of this chapter is teach how the heck we validate XYZ!)
Some parts are plain wrong, for example the part on Graph based RAG is fundamentally flawed as it assumes the text embedding and the graph embedding are in the same latent space. (This is one of many more examples).
Seems like the book was rushed, and the author has limited hands on experience (if any).
At least we know based on the amount of flaws that it was not written by an LLM
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 31, 2025
★★★★★ 5
Excellent book to truly understand LLM design patterns
Format: Paperback
I just finished reviewing Ken Huang's pocket book on LLM Design Patterns, and WOW what an amazing resource! This book is excellent if you want to truly understand how to create and enhance intelligent AI language models, all that in your pocket!
Ken makes the difficult things seem surprisingly easy, and that's the real MAGIC.
- How to prepare your data for training by making it extremely clean.
Developing the brains: the practical aspects of training, optimizing, and maintaining your models.
- Learn amazing prompting techniques (such as Chain-of-Thought and Tree-of-Thoughts) to improve your AI's reasoning and problem-solving abilities.
Learn everything there is to know about RAGs so that your LLM can incorporate outside expertise.
- It also delves into creating "agentic" AI that is capable of action and planning (not only simple plan and execute but also enhanced techniques like ReWoo!)
Really, this feels like a useful toolkit, so Ken thank you for that resource
Thanks, Idan Habler
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 9, 2025
★★★★★ 3
A Broad Overview, But Light on Modern Fine-Tuning
Format: Paperback
I'm currently really interested in fine-tuning LLMs and recently completed my first LoRA-based fine-tuning on a quantized model. I came to this book looking for more detail on fine-tuning. While it touches on the topic, I found the content didn’t quite align with the current state of the field in 2025. Techniques like LoRA, QLoRA, and PEFT weren’t really covered, and the material leaned more toward what I think are older or lower level approaches. That made it harder to connect with what I’m actually working on.
That said, when I shifted to other chapters — like the sections on prompt engineering techniques such as Chain of Thought (CoT) and Tree of Thought (ToT) — I found more value. These sections were clearer, and I picked up a few practical insights, like using few-shot examples that walk through the CoT reasoning process. That’s not something I’ve tried before, and I can see how it might help smaller models that struggle with any type of reasoning tasks.
Overall, the book feels more like a broad overview of all LLM concepts. For someone exploring many topics across the LLM ecosystem, it offers a wide-ranging introduction. But for readers like me who are actively trying to learn and apply techniques like fine-tuning and quantization, it may leave you wanting up-to-date guidance.
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Reviewed in the United States on August 10, 2025
★★★★★ 5
Great foundation read for security!
Format: Paperback
This book is a great read! It builds a strong foundation and I would highly recommend it for builders who are interetsed in building on LLMs and ensuring everything is secure. Security is super important and this book does it justice!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 27, 2025
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