Building Useful AI with RAG (Paperback)
Idioma: inglés
Editorial: Independently Published, 2026
- Tapa blanda
- Nuevo
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
Vendedor de IberLibro desde 12 de octubre de 2005
Condición: Nuevo
EUR 31,21
Cantidad disponible: 1 disponible
Añadir al carritoDescripción del artículo del vendedor
Paperback. Build AI that answers from the information you trust, not just from what a language model already knows.Large language models are powerful, but they do not automatically know your private documents, internal knowledge, product information, policies, research, or other specialized sources. Retrieval-Augmented Generation (RAG) solves that problem by connecting language models with relevant external knowledge before an answer is generated.Building Useful AI with RAG is a practical, beginner-friendly guide to understanding that workflow by building it yourself.Instead of overwhelming you with multiple frameworks, databases, and advanced techniques at once, this book focuses on the core RAG process and develops one continuous project: a Trusted Knowledge Assistant that can search a collection of documents, retrieve relevant information, and use that evidence to produce grounded answers.You will move step by step from raw documents to a complete working RAG application while understanding what each component contributes and how the pieces fit together.Inside the book, you will learn how to: Understand why language models need external knowledge and where RAG fits into modern AI applicationsPrepare and normalize trusted documents for reliable retrievalDivide documents into useful chunks without losing important contextUnderstand and create embeddings for documents and user questionsBuild a searchable vector indexUse semantic similarity to retrieve the most relevant knowledgePreserve metadata so retrieved information remains connected to its original sourceBuild reusable retrieval logic for an AI assistantCombine retrieved knowledge with a language model to create an end-to-end RAG pipelineGenerate answers that stay grounded in the available evidenceDisplay sources and handle questions the knowledge base cannot answerEvaluate retrieval quality, relevance, groundedness, and answer completenessDiagnose weak RAG results and improve chunking, queries, metadata filtering, and retrieval settingsUnderstand when hybrid search and reranking can improve resultsBuild a simple question-and-answer interface for the completed assistantUpdate and reindex the knowledge base as your documents changeThis book emphasizes understanding over copying code. You will build simple versions first, inspect how they behave, identify their limitations, and improve them deliberately. The goal is to help you understand the reasoning behind RAG well enough to adapt the workflow to your own projects instead of depending on a single framework or tool.Whether you want to build an AI assistant for company documents, product manuals, policies, technical documentation, research material, course content, or another controlled knowledge source, the same foundational workflow applies.By the end of the book, you will understand how information moves from trusted documents to retrieval, context, and finally a grounded AI answer, and you will have built the complete workflow yourself.If you are comfortable with basic Python and want to move from experimenting with language models to building useful AI applications that can answer from real knowledge, this book gives you a clear place to start. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…
N° de ref. del artículo 9798170877591
- Título
- Building Useful AI with RAG (Paperback)
- Autor
- Vincze Kalman
- Editorial
- Independently Published
- Año de publicación
- 2026
- Estado
- new
- Encuadernación
- Paperback
- Idioma
- inglés
- ISBN 13
- 9798170877591
Build AI that answers from the information you trust, not just from what a language model already knows.
Large language models are powerful, but they do not automatically know your private documents, internal knowledge, product information, policies, research, or other specialized sources. Retrieval-Augmented Generation (RAG) solves that problem by connecting language models with relevant external knowledge before an answer is generated.
Building Useful AI with RAG is a practical, beginner-friendly guide to understanding that workflow by building it yourself.
Instead of overwhelming you with multiple frameworks, databases, and advanced techniques at once, this book focuses on the core RAG process and develops one continuous project: a Trusted Knowledge Assistant that can search a collection of documents, retrieve relevant information, and use that evidence to produce grounded answers.
You will move step by step from raw documents to a complete working RAG application while understanding what each component contributes and how the pieces fit together.
Inside the book, you will learn how to:-
Understand why language models need external knowledge and where RAG fits into modern AI applications
-
Prepare and normalize trusted documents for reliable retrieval
-
Divide documents into useful chunks without losing important context
-
Understand and create embeddings for documents and user questions
-
Build a searchable vector index
-
Use semantic similarity to retrieve the most relevant knowledge
-
Preserve metadata so retrieved information remains connected to its original source
-
Build reusable retrieval logic for an AI assistant
-
Combine retrieved knowledge with a language model to create an end-to-end RAG pipeline
-
Generate answers that stay grounded in the available evidence
-
Display sources and handle questions the knowledge base cannot answer
-
Evaluate retrieval quality, relevance, groundedness, and answer completeness
-
Diagnose weak RAG results and improve chunking, queries, metadata filtering, and retrieval settings
-
Understand when hybrid search and reranking can improve results
-
Build a simple question-and-answer interface for the completed assistant
-
Update and reindex the knowledge base as your documents change
This book emphasizes understanding over copying code. You will build simple versions first, inspect how they behave, identify their limitations, and improve them deliberately. The goal is to help you understand the reasoning behind RAG well enough to adapt the workflow to your own projects instead of depending on a single framework or tool.
Whether you want to build an AI assistant for company documents, product manuals, policies, technical documentation, research material, course content, or another controlled knowledge source, the same foundational workflow applies.
By the end of the book, you will understand how information moves from trusted documents to retrieval, context, and finally a grounded AI answer, and you will have built the complete workflow yourself.
If you are comfortable with basic Python and want to move from experimenting with language models to building useful AI applications that can answer from real knowledge, this book gives you a clear place to start.
“Sinopsis” puede pertenecer a otra edición de este título.
Grand Eagle Retail
Bensenville, IL, Estados Unidos de America
Vendedor de IberLibro desde 12 de octubre de 2005
Tarifas de envío en Estados Unidos de America
| Artículo | De 6 a 14 días hábiles | De 6 a 16 días hábiles |
|---|---|---|
| Primer artículo | EUR 0,00 | EUR 0,00 |
Métodos de pago
Información empresarial del vendedor
APOLLO ONLINE CORP.
605 Geddes Street
Wilmington, DE Estados Unidos de America 19805
Condiciones de venta
We guarantee the condition of every book as it¿s described on the Abebooks web sites. If you¿ve changed
your mind about a book that you¿ve ordered, please use the Ask bookseller a question link to contact us
and we¿ll respond within 2 business days.
Books ship from California and Michigan.
Derecho al desistimiento
Si es un consumidor, puede rescindir el contrato de acuerdo con lo siguiente. Por consumidor se entiende cualquier persona física que actúe con fines ajenos a su actividad comercial, empresarial, oficio o profesión.
Información sobre el derecho de desistimiento
Derecho legal de desistimiento
Tiene derecho a rescindir este contrato en un plazo de 14 días sin dar ningún motivo.
El periodo de desistimiento vencerá a los 14 días desde que usted, o un tercero que no sea el transportista e indicado por usted, adquiera la posesión física del último bien o del último lote o pieza.
Para ejercer el derecho de desistimiento, complete de forma electrónica y envíe una declaración clara en nuestro sitio web, desde "Mis compras" en "Mi cuenta". Le enviaremos sin demora un acuse de recibo de dicho desistimiento a través de un soporte duradero (por ejemplo, por correo electrónico).
Para cumplir con el plazo de desistimiento, basta con que envíe su comunicación relativa al ejercicio del derecho de desistimiento antes de que venza el periodo de desistimiento.
Efectos del desistimiento
Si rescinde este contrato, le reembolsaremos todos los pagos que hayamos recibido de usted, incluidos los gastos de envío (excepto los gastos adicionales que surjan si elige un tipo de envío que no sea el tipo de envío estándar más económico que ofrecemos).
Podemos hacer una deducción del reembolso por la pérdida de valor de cualquier bien suministrado, si la pérdida es el resultado de una manipulación innecesaria por su parte.
Efectuaremos el reembolso sin demoras indebidas y, a más tardar, 14 días después de que se nos informe de su decisión de rescindir este contrato.
Efectuaremos el reembolso utilizando el mismo medio de pago que utilizó para la transacción inicial, a menos que haya acordado expresamente lo contrario; en cualquier caso, no incurrirá en ningún cargo como resultado de dicho reembolso.
Podremos retener el reembolso hasta que hayamos recibido los bienes o hasta que nos haya presentado una prueba de que los ha devuelto, lo que ocurra primero.
Deberá devolver los bienes o entregarlos a Grand Eagle Retail, Bensenville, Illinois, U.S.A., sin demoras indebidas y, en cualquier caso, en un plazo máximo de 14 días a partir del día en que nos comunique su desistimiento del presente contrato. El plazo se cumple si devuelve la mercancía antes de que venza el periodo de 14 días. Tendrá que asumir los gastos directos de devolución de los bienes. Usted solo es responsable de la disminución del valor de los bienes como resultado de una manipulación distinta a la necesaria para establecer la naturaleza, las características y el funcionamiento de los bienes.
Excepciones al derecho de desistimiento
El derecho de desistimiento no se aplica a lo siguiente:
- La entrega de periódicos, diarios o revistas, con la excepción de los contratos de suscripción; y
- El suministro de contenido digital que no se proporcione en un soporte tangible (por ejemplo, en un CD o DVD) si, al hacer el pedido, aceptó que podíamos empezar a entregarlo y que no podría desistir una vez iniciada la entrega.
Condiciones de envío
Orders usually ship within 2 business days. All books within the US ship free of charge. Delivery is 4-14 business days anywhere in the United States.
Books ship from California and Michigan.
If your book order is heavy or oversized, we may contact you to let you know extra shipping is required.