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13min chapter
Vectoring in on Pinecone
Practical AI: Machine Learning, Data Science, LLM
Exploring Vector Databases and RAG for Enhanced Search Operations
The chapter explains the benefits of vector databases for representing embeddings and enabling efficient search operations, diving into how RAG (Retrieval Augmented Generation) can improve response reliability by connecting user intent to structured data. It also covers advanced functionalities like namespaces and metadata filters, emphasizing the importance of metadata for filtering search results and categorizing data for different applications.
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