SKU: 6645136197

ladies captain ziegenleder damen schwarz

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Description

ladies captain ziegenleder damen schwarzDamen Pilotenjacke aus Leder mit Kunstpelzfutter, um Sie an einem Wintertag warm zu halten. Hautjacke aus Ziegenleder. Marke: Levinsky Cph. seit 1886 Material: Hauptmaterial: Ziegenleder Futter: Kunstpelz Polyester Reinigen Waschen: Nur chemische Reinigung kein Waschen Gre des Kleidungsstcks: Matabelle dieses Kleidungsstcks (cm.) Gre XS S M L XL 2XL 3XL 4XL 5XL D Gre 34 36 38 40 42 44 46 48 50 Brust 98 102 106 110 114 118 122 126 130 Hften 94 98 102

Damen-Pilotenjacke aus Leder mit Kunstpelzfutter, um Sie an einem Wintertag warm zu halten. Hautjacke aus Ziegenleder.

Marke: Levinsky Cph. seit 1886

Material:

Hauptmaterial: Ziegenleder

Futter: Kunstpelz Polyester

Reinigen/Waschen:Nur chemische Reinigung/kein Waschen

Größe des Kleidungsstücks:

Maßtabelle dieses Kleidungsstücks (cm.)
Größe XS S M L XL 2XL 3XL 4XL 5XL
D/Größe 34 36 38 40 42 44 46 48 50
Brust 98 102 106 110 114 118 122 126 130
Hüften 94 98 102 106 110 114 118 122 126


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SKU: 6645136197

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4.2 ★★★★★
Based on 10 reviews
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Product Reviews
F
Verified Purchase
Filipe Fernandes
Phoenix, 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
Chelsea, 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
B
Verified Purchase
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Already outdated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
J
Joe Faith
Lake Worth, 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.
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Reviewed in the United States on July 17, 2025
T
Tom C Taulli
Massapequa, US
★★★★★ 5
Excellent Handbook
Format: Paperback
What got my interest in this book is the author. He's well-known as a leader in the LangChain world. And his book did not disappoint. It goes through the whole life cycle of development and there is a lot useful insights. If you are looking to build real-world genAI/agentic apps, then this book is certainly a great choice.
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Reviewed in the United States on April 11, 2025

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