J-Line Plaid Cutie – Fleecedecke – Polyester – 180 x 130 cm – Mausgrau
SKU: 55174877340

J-Line Plaid Cutie – Fleecedecke – Polyester – 180 x 130 cm – Mausgrau

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Description

J-Line Plaid Cutie – Fleecedecke – Polyester – 180 x 130 cm – MausgrauPlaid Cutie Polyester Mausgrau Breite: 55cm Hhe: 10cm Lnge: 71cm Durchmesser: 55cm Gewicht: 2260g Farben: Grau Marke: J Line EAN Barcode: 5415203790071 SKU: 79007

Plaid Cutie Polyester Mausgrau
Breite: 55cm
Höhe: 10cm
Länge: 71cm
Durchmesser: 55cm
Gewicht: 2260g
Farben: Grau
Marke: J-Line
EAN/Barcode: 5415203790071
SKU: 79007
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SKU: 55174877340

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4.6 ★★★★★
Based on 330 reviews
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D
Verified Purchase
David Escobar
Los Angeles, US
★★★★★ 1
Nothing new
Format: Audiobook
There nothing new in this book you will defiantly find this content in any leadership book
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 16, 2019
F
Verified Purchase
Filipe Fernandes
Dallas, US
★★★★★ 5
Great book
Format: Paperback
Love the fact you put examples in python and javascript. Great book.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 10, 2025
E
Verified Purchase
Eddwin Paz
Belleville, US
★★★★★ 5
proper documentation from langchain
Format: Paperback
Liked the book. But Still missing Human in the loop.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 19, 2025
B
Verified Purchase
B. Black
Cuba, US
★★★★★ 3
Already outdated
Format: Paperback
Concepts are sound but the code in this book is already obsolete
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 5, 2025
J
Joe Faith
Natrona Heights, US
★★★★★ 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 17, 2025

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