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Retrieval Augmented Generation (RAG) Using Python|Hawkings J. Crowd

Retrieval Augmented Generation (RAG) Using Python : NLP And AI Applications

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Overview

Harness the potential of Retrieval Augmented Generation (RAG) to build more robust and reliable AI applications. This book provides a comprehensive, hands-on approach to implementing RAG using Python, focusing on real-world NLP and AI use cases. You'll explore:

  • The core concepts of RAG and its advantages over traditional language models.
  • Practical Python implementations using popular libraries for NLP, vector databases, and large language model APIs.
  • Techniques for efficient information retrieval, including semantic search and vector embeddings.
  • Strategies for optimizing RAG pipelines for performance and accuracy.
  • Applications in question answering, chatbots, document summarization, and more.

Whether you're a seasoned developer or just starting with AI, this book equips you with the knowledge and skills to build powerful, context-aware applications with RAG.

This item is Non-Returnable

Details

  • ISBN-13: 9798307943434
  • ISBN-10: 9798307943434
  • Publisher: Independently Published
  • Publish Date: January 2025
  • Dimensions: 9.21 x 6.14 x 0.26 inches
  • Shipping Weight: 0.41 pounds
  • Page Count: 124

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