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    3. LLM Course – Build a Semantic Book Recommender

    LLM Course – Build a Semantic Book Recommender

    Posted By: TiranaDok
    Date: 1 Aug 2025 10:32:58
    LLM Course – Build a Semantic Book Recommender

    LLM Course – Build a Semantic Book Recommender (Python, OpenAI, LangChain, Gradio) by Leandro Calado
    English | March 10, 2025 | ISBN: N/A | ASIN: B0F16LNKK9 | 76 pages | EPUB | 2.89 Mb

    LLM COURSE – BUILD A SEMANTIC BOOK RECOMMENDERPython, OpenAI, LangChain, Gradio

    Ever wondered how AI-powered book recommendation systems work? Want to go beyond simple keyword searches and build a **semantic book recommender** that actually understands books?

    This book takes you on an exciting and practical journey into the world of **LLMs (Large Language Models), embeddings, and vector search**—but with a twist. You won’t just be reading dry academic explanations. Instead, you’ll follow **Anya Sharma**, a recent CS graduate who, thanks to a mix of ambition and spite, decides to build an AI recommender to out-code her overconfident classmate, Marcus.

    Through **hands-on coding, humor, and real-world AI applications**, you will:
    • Master **embeddings and vector search** to find similar books based on content, not just keywords.
    • Use **OpenAI’s API** to generate intelligent recommendations.
    • Implement **FAISS** for real-time, scalable search.
    • Develop a functional **Gradio UI** that makes AI look pretty (or at least usable).
    • Handle AI hallucinations, optimize queries, and avoid dumb mistakes that cost money.
    If you've ever struggled with AI projects, debugging nightmares, or just want a **fun and practical guide to semantic search**, this book is for you.

    What You’ll Learn (Without Losing Your Mind):
    • **How embeddings work:** Stop guessing and start understanding how AI represents text in multi-dimensional space.
    • **The power of cosine similarity:** Discover why AI can compare books based on meaning.
    • **LLMs in action:** Summon GPT-4 like a dark sorcerer and make it analyze books intelligently.
    • **Optimizing AI for cost and performance:** Because nobody wants a recommender that bankrupts them.
    This isn’t just another AI book. It’s a **practical, entertaining, and slightly chaotic** ride through building a real-world **semantic book recommender**—one that doesn’t suck.

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