SKU: 36735893245

Armstrong Flooring Luxe w/Rigid Core Misty Day 12-in W x 24-in L x 8-mm Waterproof Interlocking Luxury Vinyl Plank Flooring (28.04-sq ft)

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Description

Armstrong Flooring Luxe w/Rigid Core Misty Day 12-in W x 24-in L x 8-mm Waterproof Interlocking Luxury Vinyl Plank Flooring (28.04-sq ft)Luxe w Rigid Core Misty Day Waterproof LVP Flooring Stone look luxury vinyl plank with a rigid WPC core and natural cork backing delivers 100% waterproof performance and low gloss comfort underfoot. The 20 mil UV acrylic wear layer resists scratches and stains, and interlocking installation makes projects fast and simple across any grade. Key Features: Waterproof Protection: Will not swell, buckle, or lose integrity when exposed to water Durable 20mil

Luxe w/Rigid Core Misty Day Waterproof LVP Flooring

Stone-look luxury vinyl plank with a rigid WPC core and natural cork backing delivers 100% waterproof performance and low-gloss comfort underfoot. The 20-mil UV acrylic wear layer resists scratches and stains, and interlocking installation makes projects fast and simple across any grade.

Key Features:

  • Waterproof Protection: Will not swell, buckle, or lose integrity when exposed to water
  • Durable 20‑mil Wear Layer: UV acrylic coating helps resist scratches, scuffs, and stains
  • Easy Interlocking Install: Floating design over concrete, wood, tile, or vinyl; no acclimation needed for most installs
  • Comfortable Rigid Core: WPC core with LVT layers and natural cork backing for quieter, cushioned steps
  • Healthy Indoor Air: FloorScore certified for low emissions

Specifications Table:

Specification Details
Series Name Luxe w/Rigid Core
Manufacturer Color/Finish Misty Day
Color/Finish Family Gray
Color Shade Medium
Pattern Stone look
Gloss Level Low
Actual Width (Inches) 12
Actual Length (Inches) 24
Actual Thickness (Millimeters) 8
Thickness Measurement 8-mm
Length Measurement 24-in
Width Measurement 12-in
Wear Layer Thickness (Mils) 20
Protective Wear Layer UV acrylic / Urethane
Square Footage Per Carton (Sq. Feet) 28.04
Square Footage Per Piece (Sq. Feet) 2
Pieces per Carton 14
Edge Type Beveled
Installation Type Interlocking
Floating Yes
Use Location Indoor
Commercial/Residential Commercial/Residential (Light Commercial approved)
Water Resistant Yes (100% Waterproof)
Scratch Resistant Yes
Stain Resistant Yes
Textured Yes
Phthalate Free Yes
For Use Over Concrete Yes
For Use Over Wood Yes
For Use Over Tile Yes
For Use Over Vinyl Yes
Variable Length No
Variable Width No
Vinyl Plank Width Wide plank (7-in+)
Style Traditional
Sold As Carton
Warranty 30-year limited
Sample Available Yes
Sample Item Number A64454B9L
UNSPSC 30161700
Luxury Vinyl Plank Yes

Frequently Asked Questions (FAQ):

Q: Can this flooring be installed in bathrooms or basements?
A: Yes. It is approved for above, on, or below grade installations and is 100% waterproof.

Q: Do I need underlayment?
A: A natural cork backing is integrated; use additional underlayment only if required by local codes or for specific sound ratings.

Q: What subfloors are compatible?
A: It can be installed over concrete, wood, tile, or existing vinyl that is clean, flat, and dry.

Q: How do I clean it?
A: Regularly clean with a damp cloth or an approved resilient floor cleaner such as Armstrong Flooring Once N' Done.

Q: Is it suitable for commercial spaces?
A: Yes, it is approved for residential and light commercial use with a 30-year limited warranty.

Soft Stone Serenity with Modern Strength

Misty Day drifts across the floor like weathered travertine, bringing a calm, layered gray palette that grounds any room. The wide 12x24 tiles create an elegant, contemporary grid that feels both tailored and organic. Pair it with matte black fixtures and warm wood accents to let the gentle movement of the design sing. This luxe LVP is the quiet luxury foundation every sophisticated space deserves.

Elevate your space with Misty Day’s waterproof, easy‑install LVP—order a carton today and start your project with confidence.

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
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  • 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
SKU: 36735893245

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4.8 ★★★★★
Based on 24 reviews
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Product Reviews
P
Verified Purchase
Par
Birmingham, US
★★★★★ 5
Excellent book on ML
Format: Paperback
This is a great book on machine learning. Topics covered are extensive - from beginner level to advanced topics including math behind different algorithms. However, not "all" algorithms are covered. Please go through the table of contents. The first part - 11 chapters - covers machine learning concepts and second part covers advanced topics with Pytorch. There are lots of excellent code and they work!! The quality of the book I received is excellent. I have gone through all 742 pages, and it has held up very well!! I used Jupyter notebook to run all examples. I created a new notebook and copied and pasted the code and ran them. This approach worked very well for me. At the same time, I could experiment with my take on the code snippets and definitely added to my knowledge. Only issue I have is on the second part of the book discussing PyTorch: (1) Some packages are a bit older version: e.g., transformer 4.9.1 whereas current version is 4.48+. It took some tweaking/recoding to get the examples working. (2) There is not much discussion on why certain architecture was chosen - e.g., number of layers, is there a rule of thumb on how to improve performance by changing these parameters? Even with CUDA the code run for a long time. Therefore, experimenting with different values of parameters become too time consuming. (3) On the same note, if I can achieve test accuracy of 90%+ using logistic regression and almost the same (perhaps one or two percent better with PyTorch with IMDB movie review dataset and that two much faster why should I use PyTorch for this dataset? Obviously, PyTorch is for certain types of problems. Discussions can be included by not adding to the exhaustive (and apt) contents. Personally I was disappointed by lack of any example on time series. Must have for ML practitioner as a reference and guide.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 20, 2024
R
Verified Purchase
Richard Hackathorn
Lexington, US
★★★★★ 5
Excellent Textbook for Hands-On Learning of ML
Format: Kindle
This textbook is for the serious life-long learners of machine learning. There are at least two ways to ‘consume’ this book. For the expert in ML, this is a textbook to study as a clear comprehensive ML overview and then to dive into sections of interest or ignorance. The concepts are grounded in code examples and are well cited (with links) to sources. Further, this textbook is appropriate if you are TensorFlow-centric and want to broaden into cutting-edge ML models/tools coded in PyTorch. For a new learner to ML, this is a textbook to DO (not just READ) with hands-on and brain-engaged. If you realize that ML is a key life-long skill for your career, consider this textbook as part of a daily learning habit (10-30 min). From personal experience, my advice to the new learner is as follows… First, clone the GitHub repository, setup your Python environment, and study the textbook, while working through the notebooks. Go on tangents and break the code. Do this methodically as part of your daily learning habit, but do not hesitate to jump ahead several chapters to prepare for tomorrow’s meeting. There is enough excellent material here for a full year of ML adventures. I did a similar strategy with Raschka’s first textbook. About four years ago, I had finished Andrew Ng’s Deep Learning Specialization as a student in his first cohort. I knew the concepts well but could not do the actual application coding. I was surprised how my Python coding improved by following Raschka’s clean and elegant style. And Raschka’s code examples were meaty enough to be springboards into working applications. Several textbook editions later, what is different about this new edition? First, it moves you through scikit-Learn (a firm foundation) to PyTorch, instead of TensorFlow. PyTorch is a better stepping-stone, both conceptually and practically. With PyTorch, you will go further with less energy, while being able to convert your efforts into TensorFlow as needed. In addition, most of the cutting-edge ML/AI/DL research is in PyTorch. It is nice to read a recent arXiv paper, clone their repository, click on the Colab tutorial, and replicate their experiments, along with picking up a ton of new coding tricks & tips. I am excited to work through these PyTorch sections to hone my skills. Second, there is a clear recognition of model tracking and tuning practices. This is often a gap in other ML textbooks and courses. Once you progress beyond the simple demo examples in a lecture, you realize that the real work is experiments, more experiments, and still more experiments, so that you must understand what the model architecture and hyperparameters are doing to your dataset. There is good coverage of scikit-Learn pipeline, grid search, model performance, and the like. Third, ML/AI/DL practice is rapidly evolving. Every week new ML packages/services become available that could save much grief on your current project. What is refreshing about Raschka’s textbook series is that he constantly adding cutting-edge topics because he likes to stay current and to help us stay current. Hence, this edition contains recent ML treats as: transformers, self-supervised learning, autoencoders-to-GAN, graph neural networks, DBSCAN, t-SNE (with brief mention of UMAP), and PyTorch-Lightning.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on February 26, 2022
A
Verified Purchase
Amazon Customer
Waukegan, US
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 10, 2025
K
Verified Purchase
Kindle Customer
Grantham, US
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 3, 2026
T
Verified Purchase
Tommy Jonsson
Phoenix, US
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 4, 2026

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