SKU: 198314891

Wild Alaska Card Pack

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Description

Wild Alaska Card PackArt is made by Felicity Rae Jones, and is printed and packaged in Homer Alaska This card pack includes one of each of the following designs: Doodle Snowy Owl, Doodle Orca, Doodle Octopus, Doodle Wolverine, Doodle Moose Skull, and Doodle Star Raven. >>>>>===========> These cards are made of a beautifully smooth paper. Being made of a thick card stock these cards are able to stand on their own while keeping a nice strait profile. Each card comes with an

Art is made by Felicity Rae Jones, and is printed and packaged in Homer Alaska

This card pack includes one of each of the following designs: Doodle Snowy Owl, Doodle Orca, Doodle Octopus, Doodle Wolverine, Doodle Moose Skull, and Doodle Star Raven.

>>>>>===========> 

These cards are made of a beautifully smooth paper. Being made of a thick card stock these cards are able to stand on their own while keeping a nice strait profile. 

Each card comes with an envelope of the same color. These are A7 cards, meaning that they are 5x7 inches when folded. The inside of the card is blank, and the card and envelope are within a protective plastic sleeve

>>>>>===========> 

Felicity Rae Jones is a self-taught artist born and raised in Homer Alaska.

She lives on her families homestead where she creates art almost every day. For her, art is an outpouring of the heart, and as her feelings splash into her creations, she strives for it to always reflect her wonder and amazement of God’s love.


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SKU: 198314891

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4.4 ★★★★★
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B. Black
West Palm Beach, 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Already outdated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
Cuba, 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
T
Tom C Taulli
Pawtucket, 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
L
Lydia O
Phoenix, US
★★★★★ 5
Useful resource!
Format: Paperback
I found this book well written and extremely useful for getting comfortable with LLMs for building AI apps in production and other agent driven applications.
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Reviewed in the United States on April 10, 2025
J
Jacob Lee
Natrona Heights, US
★★★★★ 5
Fantastic!
Format: Paperback
A great primer on getting started with LangChain concepts!
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Reviewed in the United States on April 10, 2025

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