SKU: 1107717698
corner hanging plant stand

corner hanging plant stand 4-Tier Plant Stand, Multiple Potted Plants Holder Corner Flower Shelf

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Description

corner hanging plant stand 4-Tier Plant Stand, Multiple Potted Plants Holder Corner Flower ShelfSturdy Flower Display Stand Crafted with an E1 particle board and a powder coated metal frame, this corner plant shelf is sturdy and durable. Its smooth, waterproof and scratch resistant surface is easy to maintain. Stylish & Adjustable Design Our elegant 4 tier plant stand features staggered, irregular elements creating a stylish aesthetic. The circular design rotates freely, ensuring maximum exposure to sunlight for your plants. Space Efficient

Sturdy Flower Display Stand - Crafted with an E1 particle board and a powder-coated metal frame, this corner plant shelf is sturdy and durable. Its smooth, waterproof and scratch-resistant surface is easy to maintain.

Stylish & Adjustable Design - Our elegant 4 tier plant stand features staggered, irregular elements creating a stylish aesthetic. The circular design rotates freely, ensuring maximum exposure to sunlight for your plants.

Space-Efficient Plant Holder - Ideal for corners, our stand has 4 round trays (each with a diameter of 9.44"), perfect for small to medium-sized plants, bonsai and planters. Overall size: 19.68" L x19.68" W x 40.94" H. Suitable for indoor use.

Easy Assembly - This industrial 4-tier plant stand can be assembled with ease, in less than 10 minutes, using the provided directions and included tools.

Customer Support - For any issues or dissatisfaction, reach out to us for prompt assistance. Our stand comes with an 18-month warranty and professional customer service.

Product Dimensions & Weights Details
Length 19.68"
Depth 19.68"
Height 40.94"
Item Weight 13.12 lbs

Packaging Dimensions & Weights
  • 25.59" L x 22.44" W x 3.54" H (15.21 lbs)

Installation Guide.pdf

Installation Guide Video:

 

Details of this Flower Shelf

Water-proof Surface

Made of smooth particle board without burr and the surface has been processed by coating and waterproof treatment, it is anti-corrosion and easy to clean.

Strong Metal Construction

This cute plant holder is constructed of thick heavy-duty metal frame, which provides a strong capacity and makes it solid and sturdy.

Adjustable Foot Pads

The feet of the planter shelf can be adjusted to adapt to different grounds, keep it stable without shaking.

5-tier Design

The high low designed planter shelf works great with all varieties of plants, whether palm trees, cacti, succulents, or fiddle leaf figs.


Product Information
Finish Type Powder Coated
Shape Round
Base Type Leg
Assembly Required Yes
Number of Levels 4
Product Dimensions 19.68 x 19.68 x 40.94 inches
Item Weight 13.2 pounds
Finish types Powder Coated
Batteries required No
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Exchange/Return Notes
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SKU: 1107717698

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4.4 ★★★★★
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Verified Purchase
Zygerian99
West Palm Beach, US
★★★★★ 5
The definitive guide to becoming a researcher in the field
Format: Hardcover
This is not a coding book. I see a lot of negative reviews around the expectation that this book would teach the reader how to quickly build machine learning systems and write code. This book is not for that audience. If you just want to build applications, don't worry about how deep learning works. It's akin to needing to understand how an engine works just to drive a car. If you are looking for a coding resource, try: https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1492032646/ref=sr_1_4?keywords=machine+learning+tensorflow&qid=1579608765&sr=8-4 . And even with that book, the material still goes far beyond what you need - use it as a light reference. I bought this book as an aspiring machine learning researcher, and towards that end, it is the best resource available in print (still true as of 2020). For instance: The first 5 chapters are timeless. These are things that were mostly established 20 or 30 years ago and beyond and are mostly STEM fundamentals at this point. There are whole textbooks dedicated to each of those chapters, but the authors provide a quick refresher and overview of probably 80% of what you'll encounter in deep learning. If you haven't previously learned each of these subtopics, you'll probably want to study them individually since they are the key to innovating (linear algebra, probability & stats, numerical computation, machine learning fundamentals). Chapters 6 thru 9 are the foundation of deep learning. We're about 12 years into seeing rapid change in the deep learning space, yet all of these principles and techniques still hold (many recent innovations are still relying on Convolutional models in 2020, which is the most layered/complex topics in those chapters). Therefore, I'd wager that these chapters are also fairly stable knowledge that is worth internalizing if you want to be deeply involved in the future of machine learning. Chapters after 9 are mostly experimental topics, and many of them are already the wrong strategies for optimal results. But there are interesting ideas in here that you'll often encounter in the wild, so it's good exposure to various topics. But probably not worth much of your time. And lastly, there is good history in here from people who know the space intimately. It's a good way to piece together the developments and learn the lexicon of deep learning so you can have intelligent conversation with experts.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on January 21, 2020
S
Verified Purchase
Shannon
Louisville, US
★★★★★ 5
The best DL/ML book I have ever seen!!
Format: Hardcover
Fantastic deep-learning book! The logic is very easy to follow, but the content is very thorough when it comes to explaining the theories behind it, making it perfect for beginners as well as math and CS students. The best DL/ML book I have ever seen!!
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Reviewed in the United States on November 30, 2025
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Verified Purchase
William P Ross
Battle Creek, US
★★★★★ 5
Comprehensive Look At An Incredibly Complex Topic
Format: Hardcover
Deep Learning is an advanced book with great explanations and details. There is a heavy math focus with the book's beginning chapters detailing the necessary linear algebra and probability that one will need to understand deep learning. I liked that the author's chose to cover only the parts of these subjects which are relevant to deep learning. There are many interesting philosophical sections in the book as well. Just about when I was feeling overwhelmed with the complexity of the mathematics the authors take a step back and cover the foundations of deep learning such as borrowing concepts from human learning. There was an interesting dicussion about the early studies done on the vision of cat's and monkey's in the 1970s. The text covers the entire history of deep learning and the bibliography is hundreds of sources. It is clear this is the most comprehensive text available about deep learning. For anybody interested in this topic this book is a mandatory read. There are sections about machine learning as well, which makes sense because deep learning is a subset of machine learning. These sections focused on the machine learning concepts which are most relevant to deep learning. The book was well organized and divided into three parts which cover mathematics related to deep learning, typical deep learning techniques, and then more experiment learning techniques. Often the author's state when a technique works well or when it does not, and which types of data works best for the technique. Just a warning, the math in this book is highly complex. It requires a lot of work to go through this book, but the effort will be well rewarded.
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Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
Grantham, US
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry. The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
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Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Port Orchard, US
★★★★★ 5
Comprehensive! The Bible of Deep Learning!
This book has by far surpassed my expectations! I have purchased many machine learning and deep neural network books in the past, but nothing has ever come close to this book! First of all, it is written by the fathers of Deep Learning, and is therefore an authority. Secondly, the book is broken into three parts: 1. A math overview and refresher. 2. Deep Learning applications and 3. Research in Deep Learning. I can't help but go through this book from front to back. It is a smooth read, and every sentence written is meaningful. These guys know their stuff! And after you read this book, YOU WILL ALSO know your stuff! If you feel daunted by the price, just remember, you get what you pay for! I'd say they could easily charge about $300+ for this book, but they are doing everyone a very kind favor by ONLY charging this reasonable amount. You get A LOT of bang for your buck with this purchase. I hesitated at first about buying this book because of the price, but I am soooooo happy that I did! Worth every penny! Look no further, get this book and start your Deep Learning journey!!
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Reviewed in the United States on July 14, 2017

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