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    RAG-Driven Generative AI. Build custom retrieval augmented generation pipelines with LlamaIndex, Deep Lake, and Pinecone

    (ebook) (audiobook) (audiobook) Język publikacji: angielski
    Autor:
    Denis Rothman
    RAG-Driven Generative AI. Build custom retrieval augmented generation pipelines with LlamaIndex, Deep Lake, and Pinecone Denis Rothman - okładka ebooka

    RAG-Driven Generative AI. Build custom retrieval augmented generation pipelines with LlamaIndex, Deep Lake, and Pinecone Denis Rothman - okładka ebooka

    RAG-Driven Generative AI. Build custom retrieval augmented generation pipelines with LlamaIndex, Deep Lake, and Pinecone Denis Rothman - okładka audiobooka MP3

    RAG-Driven Generative AI. Build custom retrieval augmented generation pipelines with LlamaIndex, Deep Lake, and Pinecone Denis Rothman - okładka audiobooks CD

    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    200
    +99 pkt
    Designing and managing controlled, reliable multimodal generative AI pipelines is complex. RAG-Driven Generative AI provides a roadmap for building effective LLM, computer vision, and Generative AI systems that will balance performance and costs.

    From foundational concepts to complex implementations, this book offers a detailed exploration of how RAG can control and enhance AI systems by tracing each output to its source document. RAG’s traceable process allows human feedback for continual improvements, minimizing inaccuracies, hallucinations, and bias. This AI book shows you how to build a RAG framework from scratch, providing practical knowledge on vector stores, chunking, indexing, and ranking. You’ll discover techniques to optimize performance and costs, improving model accuracy by combining with human feedback, managing costs with when to fine-tune, and improving accuracy and retrieval speed by combining with embedded-indexed knowledge graphs.

    Experience a blend of theory and practice using frameworks like LlamaIndex, LangChain, Pinecone, and Deep Lake and models from Hugging Face, OpenAI, and Google Vertex AI.

    By the end of this book, you will have acquired the skills to implement intelligent solutions, keeping you competitive in fields from production to customer service across any project.

    Wybrane bestsellery

    O autorze ebooka

    Denis Rothman graduated from Sorbonne University and Paris-Diderot University, designing one of the very first word2matrix patented embedding and patented AI conversational agents. He began his career authoring one of the first AI cognitive natural language processing (NLP) chatbots applied as an automated language teacher for Moët et Chandon and other companies. He authored an AI resource optimizer for IBM and apparel producers. He then authored an advanced planning and scheduling (APS) solution used worldwide.

    Denis Rothman - pozostałe książki

    Oceny i opinie klientów: RAG-Driven Generative AI. Build custom retrieval augmented generation pipelines with LlamaIndex, Deep Lake, and Pinecone Denis Rothman (0) Weryfikacja opinii następuję na podstawie historii zamówień na koncie Użytkownika umieszczającego opinię. Użytkownik mógł otrzymać punkty za opublikowanie opinii uprawniające do uzyskania rabatu w ramach Programu Punktowego.

    Packt Publishing - inne książki

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