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Description
Ashley Express - Limited Edition Plush MattressLuxury comfort leads to luxury rest. Wake up refreshed and ready to take on the day with this plush queen mattress. Packed inside are layers of ultra soft and supportive foam to relieve your pressure points. Rows of power packed wrapped coils support you night after night. So snooze awaywith this mattress, you'll treat yourself to a truly restorative sleep experience. Specifications Details Comfort level: plush, Luxury cotton fiber; super support
Luxury comfort leads to luxury rest. Wake up refreshed and ready to take on the day with this plush queen mattress. Packed inside are layers of ultra-soft and supportive foam to relieve your pressure points. Rows of power packed wrapped coils support you night after night. So snooze away—with this mattress, you'll treat yourself to a truly restorative sleep experience.Specifications
| Details | Comfort level: plush, Luxury cotton fiber; super support polyester fiber, Super-soft quilt foam, Comfort plush support foam, High-density gel support memory foam; high-density base foam, 680 power packed 15-gauge wrapped coils, Ashley edge "steel encased"; 2 perimeter rows of 13-gauge wrapped coils for edge support, 4-way stretch knit cover, 10-year non-prorated warranty, Note: Purchasing mattress and foundation from two different brands may void warranty; check warranty for details, Foundation/box spring available, sold separately, Mattress ships in a box; please allow 48 hours for your mattress to fully expand after opening, State recycling fee may apply | |
| Material | Fabric | |
| Lifestyle | Traditional | |
| Weight | 90 | |
| Weight_unit | Pound | |
Twin Specifications
| Dimensions | 75''W x 38''D x 14''H | |
Full Specifications
| Dimensions | 75''W x 53''D x 14''H | |
Queen Specifications
| Dimensions | 80''W x 60''D x 14''H | |
King Specifications
| Dimensions | 80''W x 76''D x 14''H | |
California King Specifications
| Dimensions | 84''W x 72''D x 14''H | |
Twin XL Specifications
| Dimensions | 80''W x 38''D x 14''H | |
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4.2 ★★★★★
Based on 22 reviews
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Product Reviews
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 5
Unlocking Practical AI: A Developer’s Guide to Building with LLMs and LangChain
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