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Jdypisa S/s Print Top Jrs Noos - Ecru DessinDit ecru dessin t shirt van Jacqueline de Yong is een must have voor elke dames garderobe. Het is gemaakt van 100% biologisch katoen, wat niet alleen zacht en comfortabel is om te dragen, maar ook goed is voor het milieu. Het t shirt heeft korte mouwen en een klassiek ronde hals, waardoor het gemakkelijk te combineren is met verschillende outfits. Het dessin geeft een speels tintje aan het shirt, waardoor het perfect is voor zowel casual als geklede
Dit ecru dessin t-shirt van Jacqueline de Yong is een must-have voor elke dames garderobe. Het is gemaakt van 100% biologisch katoen, wat niet alleen zacht en comfortabel is om te dragen, maar ook goed is voor het milieu. Het t-shirt heeft korte mouwen en een klassiek ronde hals, waardoor het gemakkelijk te combineren is met verschillende outfits. Het dessin geeft een speels tintje aan het shirt, waardoor het perfect is voor zowel casual als geklede gelegenheden. Met dit t-shirt van Jacqueline de Yong ben je niet alleen fashionable, maar ook nog eens duurzaam bezig! Bestel nu en voeg deze must-have toe aan je kledingkast.Shipping Notes
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4.5 ★★★★★
Based on 1769 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Already outdated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