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Applied RAG - Practical Retrieval-Augmented Generation with Python: A Comprehensive Guide to Building Knowledge-Grounded AI Applications - Tapa blanda
Sinopsis
Applied RAG: Practical Retrieval-Augmented Generation with Python, authored by Dr. Balaji Venkateswaran, provides a hands-on blueprint for building reliable, knowledge-grounded AI systems. The book addresses LLM limitations like hallucination and static knowledge, guiding readers through RAG theory, architecture, and practical Python workflows. It covers building blocks such as retrievers and embeddings, advanced retrieval techniques, and integration with frameworks like LangChain. Real-world applications, operational challenges, evaluation, security, and ethical AI are emphasized. This book empowers engineers, scientists, and leaders to master RAG and innovate in creating robust, up-to-date AI solutions for tasks such as QA, summarization, and agents for enterprises.
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Applied RAG - Practical Retrieval-Augmented Generation with Python: A Comprehensive Guide to Building Knowledge-Grounded AI Applications
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Applied RAG - Practical Retrieval-Augmented Generation with Python
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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: L2-9798900541341
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Applied RAG - Practical Retrieval-Augmented Generation with Python
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Applied RAG - Practical Retrieval-Augmented Generation with Python (Paperback)
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Paperback. Condición: new. Paperback. Applied RAG: Practical Retrieval-Augmented Generation with Python, authored by Dr. Balaji Venkateswaran, provides a hands-on blueprint for building reliable, knowledge-grounded AI systems. The book addresses LLM limitations like hallucination and static knowledge, guiding readers through RAG theory, architecture, and practical Python workflows. It covers building blocks such as retrievers and embeddings, advanced retrieval techniques, and integration with frameworks like LangChain. Real-world applications, operational challenges, evaluation, security, and ethical AI are emphasized. This book empowers engineers, scientists, and leaders to master RAG and innovate in creating robust, up-to-date AI solutions for tasks such as QA, summarization, and agents for enterprises. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798900541341
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Applied RAG - Practical Retrieval-Augmented Generation with Python : A Comprehensive Guide to Building Knowledge-Grounded AI Applications
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Taschenbuch. Condición: Neu. Neuware - Applied RAG: Practical Retrieval-Augmented Generation with Python, authored by Dr. Balaji Venkateswaran, provides a hands-on blueprint for building reliable, knowledge-grounded AI systems. The book addresses LLM limitations like hallucination and static knowledge, guiding readers through RAG theory, architecture, and practical Python workflows. It covers building blocks such as retrievers and embeddings, advanced retrieval techniques, and integration with frameworks like LangChain. Real-world applications, operational challenges, evaluation, security, and ethical AI are emphasized. This book empowers engineers, scientists, and leaders to master RAG and innovate in creating robust, up-to-date AI solutions for tasks such as QA, summarization, and agents for enterprises. Nº de ref. del artículo: 9798900541341
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