Pay in installments of $7.00 with
,
and
Shipping Estimate
USA
- USA
- CAN
- USA
- CAN
Ships within 48 hours · Estimated delivery Sep 8 - Sep 13
Promo Codes Available:
For Your Every Summer RSVP, with Code: SUMMER15
Description
lego store money tree LEGO® Money Tree Building Kit 40648Pieces: 336 Ages: 9+ Years Model Number: 40648 Description: Encourage creativity with the LEGO Money Tree (40648) building kit for kids, which lets boys and girls aged 9 and up celebrate Lunar New Year while assembling a beautiful piece of LEGO seasonal decor. Builders can immerse themselves in tradition as they create the money tree model and discover its awesome details. In Chinese culture it has long been believed that a money tree brings
Pieces: 336
Ages: 9+ Years
Model Number: 40648
Description:
Encourage creativity with the LEGO® Money Tree (40648) building kit for kids, which lets boys and girls aged 9 and up celebrate Lunar New Year while assembling a beautiful piece of LEGO seasonal decor. Builders can immerse themselves in tradition as they create the money tree model and discover its awesome details. In Chinese culture it has long been believed that a money tree brings abundance, prosperity and good luck and, true to this belief, this LEGO tree is adorned with riches and rewardsincluding 20 tangerines, 14 red envelopes and 10 coins. Once it’s complete, the model becomes an eye-catching piece of Lunar New Year decor that can be displayed in any room or used as a table centerpiece. A thoughtful gift idea for kids, this building set is sure to delight everyone who celebrates the festival or would like to learn more about it.
- Building kit for kids – Celebrate Lunar New Year with the LEGO® Money Tree building set for boys and girls aged 9 and up
- Decorative features – The money tree is adorned with 20 tangerines, 14 red envelopes and 10 coins to represent prosperity and good luck
- Easy to display – The toy tree features a red base, making it easy to display at home or in an office
- Gift for kids – This seasonal building set can be given as a Lunar New Year gift for those who celebrate the occasion or would like to learn more about it
- LEGO® decor – Once it’s complete, the tree makes an eye-catching piece of seasonal decor that can be showcased at home or used as a table centerpiece
- Continue the fun – Check out other building sets (sold separately) inspired by traditional festivals
- Dimensions – The money tree measures over 6 in. (16 cm) high
Shipping Notes
- Free Standard Shipping on $100+ Orders to the USA.
- Except Preorder products are shipped in 48 hours.
- Delivery to the USA:
- Standard Shipping : 3-10 business days
- If time is of the essence, please consider selecting expedited delivery for faster service.
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]
- Please click here for more details>>> Return & Exchange Policy
4.4 ★★★★★
Based on 23 reviews
Sort
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.
WAS THIS REVIEW HELPFUL?YesReportShare
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
recommand products
Fiddle Leaf Fig Tree 5.5’
20.05
5FT 6FT Fiddle Leaf Fig Faux Tree Artificial Fiddle Leaves Banjo Fig Realistic Figuier Lyre Plant with White Pot, for Indoor Outdoor Decor, Home
22.58
Fiddle Leaf Fig Bush Houseplant
21.93
Elegant Green Fiddle Leaf Fig Artificial plant
21.89
Peperomia Prostrata - ‘String of Turtles’
24.22