9798900541341 - applied rag - practical retrieval-augmented generation with python: a comprehensive guide to building knowledge-grounded ai applications di dr. balaji venkateswaran (5 risultati)

- Brossura
Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 19,50
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.

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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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EUR 22,35
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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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EUR 19,51
EUR 5,85 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 28,89
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Taschenbuch. Condizione: 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 R…AG 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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- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
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EUR 23,40
EUR 43,15 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: 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 RA…G 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.