SKU: 35966213480

Madison Celeste 24 in. x 24 in. Polished Porcelain Stone Look Floor and Wall Tile (16 sq. ft./Case)

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Description

Madison Celeste 24 in. x 24 in. Polished Porcelain Stone Look Floor and Wall Tile (16 sq. ft./Case)This porcelain tile is perfect for both residential and commercial use, with a grade 1 rating and a glazed polished finish. Measuring 24 in. x 24 in. and 10 mil thick, it offers a high sheen and slight variation in tone. Each case contains four pieces, covering 16 sq. ft., with a case weight of 68. 84 lbs. This tile is suitable for medium duty floors and is impervious to water, with a P. E. I. Rating of III. With a C. O. F. greater than 0. 50, it is

This porcelain tile is perfect for both residential and commercial use, with a grade 1 rating and a glazed polished finish. Measuring 24 in. x 24 in. and 10 mil thick, it offers a high sheen and slight variation in tone. Each case contains four pieces, covering 16 sq. ft., with a case weight of 68.84 lbs. This tile is suitable for medium-duty floors and is impervious to water, with a P.E.I. Rating of III. With a C.O.F. greater than 0.50, it is recommended for standard applications and is marginally skid resistant. It is completely frost resistant and can be used indoors or outdoors with a latex-modified thinset for optimal bond strength.

Dimensions

Approximate Tile Size

24x24

Product Length (in.)

24 in

Product Thickness (mm)

10 mm

Product Width (in.)

24 in

Suggested Grout Line Size

1/8

Details

Application Location

Floor, Wall

Break Strength (lb.)

300

Color Family

Gray

Color/Finish

Madison Celeste

Commercial / Residential

Commercial / Residential

DCOF Rating

Less than 0.42

Edge Type

Rectified

Flooring Look

Stone Look

Flooring Product Type

Porcelain Tile

Indoor/Outdoor

Indoor, Outdoor

Installation Method

Mortar

Location

Bathroom, Fireplace, Garage, Kitchen, Shower

Minimum Acclimation Period

No Acclimation Required

Returnable

90-Day

Tile Features

Frost Resistant, Radiant/Underfloor Warming Heating

Tile Finish

Polished

Tile Format

Standard

Tile Material

Porcelain

Water Protection

Waterproof

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SKU: 35966213480

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Verified Purchase
David Escobar
Battle Creek, US
★★★★★ 1
Nothing new
Format: Audiobook
There nothing new in this book you will defiantly find this content in any leadership book
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Reviewed in the United States on November 16, 2019
F
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Filipe Fernandes
Los Angeles, US
★★★★★ 5
Great book
Format: Paperback
Love the fact you put examples in python and javascript. Great book.
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Reviewed in the United States on June 10, 2025
E
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Eddwin Paz
Draper, US
★★★★★ 5
proper documentation from langchain
Format: Paperback
Liked the book. But Still missing Human in the loop.
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Reviewed in the United States on April 19, 2025
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B. Black
Fort Morgan, US
★★★★★ 3
Already outdated
Format: Paperback
Concepts are sound but the code in this book is already obsolete
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Reviewed in the United States on August 5, 2025
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Bozeman, US
★★★★★ 5
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Format: Paperback
If you're a developer eager to move beyond LLM experimentation and build robust, context-aware AI applications, this book offers both inspiration and practical guidance. The authors open with a clear passion for the transformative potential of large language models (LLMs) and LangChain, framing these technologies as not just enhancements to the developer’s toolkit, but as gateways to new kinds of “thing-building” superpowers. This sense of possibility is grounded in step-by-step instruction, making the book approachable for those with Python or JavaScript backgrounds who may be new to the world of production-grade AI agents. What stands out is the book’s careful scaffolding: starting with foundational concepts like prompt-based programming and progressing to advanced capabilities such as retrieval-augmented generation, agent planning, and tool integration. Each stage is contextualized with real-world use cases, like customizing chatbots to interact with your own documents, personalizing user experiences through memory, and deploying to production with reliability and security in mind. The focus on chain-of-thought reasoning and LangGraph’s agent architecture demonstrates the authors’ awareness of the current state of AI, where context and planning are just as important as raw language ability.
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Reviewed in the United States on July 17, 2025

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