SKU: 87483964538

Flexco Buff 4.5-in x 480-in Vinyl Floor Base

Sale price$122.60 Regular price$136.22
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Description

Flexco Buff 4.5-in x 480-in Vinyl Floor BaseBuff 4. 5 in x 480 in Vinyl Wall Base Durable PVC vinyl wall base in Buff provides a clean, finished transition between floor and wall. At 4. 5 in high and 40 ft long, its designed for glue down installation in residential or commercial spaces. Key Features: Durable Vinyl Construction: PVC compound with non phthalate plasticizer for long lasting performance Clean Finished Look: Smooth profile helps conceal minor floor and wall irregularities Scuff and

Buff 4.5-in x 480-in Vinyl Wall Base

Durable PVC vinyl wall base in Buff provides a clean, finished transition between floor and wall. At 4.5 in high and 40 ft long, it’s designed for glue-down installation in residential or commercial spaces.


Key Features:

  • Durable Vinyl Construction: PVC compound with non-phthalate plasticizer for long-lasting performance
  • Clean Finished Look: Smooth profile helps conceal minor floor and wall irregularities
  • Scuff- and Chemical-Resistant: Homogeneous color and superior finish resist scuffing, gouging, and most chemicals
  • Easy Installation: Glue-down application for indoor use in homes or commercial settings
  • Made in the USA: Quality manufacturing with a 2-year limited warranty

Specifications Table:

Specification Details
Color Buff
Manufacturer Color/Finish Buff
Color/Finish Family Off-white
Color Shade Light
Finish Type Painted
Series Name Wall Base
Type Wall base
Material Vinyl (PVC, non-phthalate plasticizer)
Height/Width 4.5 in
Length 480 in (40 ft)
Thickness 0.125 in (1/8 in)
Installation Type Glue down
Pattern Smooth
Water Resistant Yes
Waterproof No
For Use With Hardwood, Laminate, Vinyl
Indoor/Outdoor Indoor use only
Warranty 2-year limited
Country of Origin USA
UNSPSC 47121600

Frequently Asked Questions (FAQ):

Q: How is this wall base installed?
A: It is designed for glue-down installation on indoor walls; use a compatible wall base adhesive per manufacturer directions.


Q: Is the color through-body or just on the surface?
A: The color is homogeneous through the base, helping hide scratches and wear.


Q: Can it be used in bathrooms or kitchens?
A: Yes, it is water-resistant vinyl and suitable for indoor residential or commercial spaces; it is not waterproof.


Q: What are the dimensions?
A: 4.5 inches high and 480 inches (40 ft) long with a 1/8-in (0.125-in) thickness.


Q: Is this safe from phthalates?
A: Yes, it uses a PVC compound with a non-phthalate plasticizer.


A Seamless, Soft-Neutral Finish for Every Floor Line

In a gentle Buff tone, this wall base draws the eye in a quiet, architectural gesture—crisp, smooth, and impeccably tailored. I love how its uniform 4.5-inch height frames a room and tidies transitions without visual clutter. Pair it with textured stone or warm oak planks to let the hue whisper sophistication while grounding the palette. It’s a refined essential that elevates everyday spaces into polished, livable luxury.


Finish your room with a sleek, durable Buff wall base that installs easily and elevates any space—add it to your project today.

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SKU: 87483964538

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4.6 ★★★★★
Based on 27 reviews
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Shannon
Massapequa, 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!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 30, 2025
W
Verified Purchase
William P Ross
Carnegie, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
Cuba, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Lowell, 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
M
Verified Purchase
mackster
Dallas, US
★★★★★ 1
A rushed, poorly written guide of how the "experts" can't really explain what Deep Learning is
Format: Hardcover
This book, in every sense of the word, is rushed. I think the authors wanted to establish themselves as leaders of this young-ish field, but does so by sacrificing quality. It also shows that Deep Learning theory has been there for a long time, known by another name called Neural Networks. The interesting algorithms are of MLP, Back Propagation and the classical neural networks. The optimization methods such as Adam are the ones that are new and interesting, and the only ones worthy of in this book. So, essentially, what you get from this book is use A for X, B for Y and C for Z type of dry, un-intuitive, badly written waste of paper. As for the structure of the book, it's like an example of how not to structure a book. It has some linear algebra, probability at the start (not good enough, and confuses more people and wastes paper). Goes on to prove other algorithms such as PCA (yeah, ok!). Then, talks about how this architecture works for this and that architecture. So, yeah, if you really want to try out deep learning, don't buy this book. Set up Tensorflow/pytorch/ other library, run the tutorials, find an architecture for the problem you are interested in and start tweaking that. You will have far more fun and would have saved your money. The praise that this book gets is beyond me. Did Musk even read this book? I doubt it.
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Reviewed in the United States on May 15, 2018

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