Mid Century Esavian James Leonard School Drawers - 1305e
SKU: 59745203792

Mid Century Esavian James Leonard School Drawers - 1305e

$582.75 $647.50
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Description

Mid Century Esavian James Leonard School Drawers - 1305eA scarcely seen Mid Century chest of school drawers designed by James Leonard in the early 1950's for Esavian (ESA) The Educational Supply Association. Excellent restored condition A very versatile piece of storage with twenty equally sized drawers with striking cutaway handles this triangular design being much rarer than the oval style. The carcass of this beautiful piece of furniture is constructed from beech, the drawers are also constructed from

A scarcely seen Mid Century chest of school drawers designed by James Leonard in the early 1950's for Esavian (ESA) The Educational Supply Association.

– Excellent restored condition

A very versatile piece of storage with twenty equally sized drawers with striking cutaway handles - this triangular design being much rarer than the oval style.

The carcass of this beautiful piece of furniture is constructed from beech, the drawers are also constructed from solid beech.

A stunning example of Mid Century furniture, and one of our absolute favourites.

We have sympathetically restored these drawers to retain their stunning original character. They have been lightly sanded back and oiled resulting in a stunning piece with a rich, warm finish.

Condition
These drawers are vintage and have had years of use in schools by children so they do come with imperfections. They will have marks, polished in scratches, nics and the odd dink here and there... which add to their character, vintage appeal and gives a unique aged look - something that new furniture cannot replicate! There are marks etc inside the drawers but these could be easily lined with a paper of your choice if desired. Please see the photos for more detail.

Dimensions:

Width: 122cm  

Height: 78cm

Depth: 36cm


Drawers - internal:  

Width: 24.5cm 

Height: 10cm  

Depth: 29cm


This beautiful piece of furniture has been brought into our workshop and lovingly restored by hand. We use our skills and years of experience to ensure that every piece retains all of its quality and much loved character & warmth. When it leaves our workshop it is ready to start a new life, in your home, to be enjoyed by generations to come.

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SKU: 59745203792

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4.2 ★★★★★
Based on 2064 reviews
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Product Reviews
O
Om S
Omaha, US
★★★★★ 4
Title: Really Good Book for Learning LLMs
Format: Paperback, Format: Paperback
I picked up this book after struggling with LLM implementation at work. Ken Huang explains things clearly without too much technical jargon. The book covers everything from data preparation to building AI agents. I especially liked the chapters on RAG and prompting techniques - they helped me improve my current projects. The code examples actually work, which is nice. Some parts are pretty advanced, so you need basic Python knowledge. I had to read a few chapters twice to fully get it. The fairness and bias detection section was eye-opening. Good practical advice throughout. Not just theory - real solutions you can use. Worth the money if you're serious about LLM development. Recommended for anyone building AI systems professionally.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 25, 2025
J
Jiewen Wang
Fort Morgan, US
★★★★★ 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
N
Nader
New York, US
★★★★★ 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
N
noam barkay
San Leandro, US
★★★★★ 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
R
Ryan Meyer
Whiting, US
★★★★★ 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

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