Vector Databases for Developers: Hands-On Implementation of Embedding-Based Search Engines and LLM Retrieval with Python, (Paperback)

<p><b>Unlock the Power of Vectors in AI Applications</b><br>Discover how modern developers are building intelligent search and retrieval systems with embeddings, vector databases, and Python-powered APIs.</p><p><br>Vector databases are at the heart of AI-native applications from semantic search to RAG-powered LLM systems. This hands-on guide empowers developers to build real-world, production-ready vector search engines using Python, FastAPI, and open-source tools.</p><p>Inside, you'll learn how to generate embeddings, store them efficiently, and build scalable retrieval systems using top-tier vector databases like FAISS, Qdrant, Milvus, and Pinecone. Through structured chapters and practical code examples, the book walks you through indexing strategies, similarity search, LLM integration, and full-stack deployment all from a developer's perspective.</p><p>Whether you're developing custom search engines, recommendation systems, or AI chatbots, this book offers the practical foundation and tools you need to confidently implement vector-based solutions in your software projects.</p><p><b>Key Features: </b></p><ul><li><p>Step-by-step tutorials on FAISS, Qdrant, Weaviate, Milvus, and Pinecone</p></li><li><p>Build and deploy LLM-integrated search pipelines using FastAPI</p></li><li><p>Master embedding generation with Hugging Face and OpenAI</p></li><li><p>Design scalable architectures for production-ready retrieval systems</p></li><li><p>Hands-on examples with code that's ready to adapt and extend</p></li></ul><p>Start developing the next generation of AI-powered applications. <i>Grab your copy</i> <i>of</i> "<b>Vector Databases for Developers</b>" <i>today</i>!</p>

• Vector Databases for Developers: Hands-On Implementation of Embedding-Based Search Engines and LLM Retrieval with Python, (Paperback)
• Author: Independently Published
• ISBN: 9798294333560
• Format: Paperback
• Publication Date: 2025-07-26
• Page Count: 150