Name: Vector Databases and RAG with Python. Build intelligent search and retrieval systems using embeddings and LLMs (en Inglés)
SKU: 68486525
Price: 52.94 USD
Availability: InStock
Author: Rajdeep Dua

portada Vector Databases and RAG with Python. Build intelligent search and retrieval systems using embeddings and LLMs (en Inglés)

Vector Databases and RAG with Python. Build intelligent search and retrieval systems using embeddings and LLMs (en Inglés)

Formato

Libro Físico

Editorial

BPB Publications

Autor

Rajdeep Dua

Año

2026

Idioma

Inglés

N° páginas

334

Encuadernación

Tapa Blanda

Dimensiones

23.5x19.1 cm

ISBN13

9789378545689

Vector Databases and RAG with Python. Build intelligent search and retrieval systems using embeddings and LLMs (en Inglés)

Rajdeep Dua (Autor) · BPB Publications · Tapa Blanda

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Reseña del libro "Vector Databases and RAG with Python. Build intelligent search and retrieval systems using embeddings and LLMs (en Inglés)"

This comprehensive guide takes you from foundational concepts to production-ready implementations of vector databases and RAG systems. Starting with vector semantics and embeddings, you will learn to generate vector representations using neural networks, BERT, and OpenAI models. The book covers popular vector databases including Weaviate and Milvus, teaching you how to implement efficient search algorithms like k-nearest neighbors and hierarchical navigable small worlds. You will build complete RAG pipelines, explore advanced techniques like GraphRAG, and master evaluation frameworks using LlamaIndex. Each chapter includes hands-on Python examples with practical code implementations that demonstrate real-world applications.

As large language models continue to transform how we build intelligent systems, the ability to integrate proprietary data through vector search and RAG has become essential for creating accurate, contextually-aware applications that go beyond the limitations of pre-trained models.