Chunking is a critical step in designing a Retrieval-Augmented Generation (RAG) application as it enhances the efficiency and accuracy of the retrieval process. The post discusses five chunking strategies: fixed-size, semantic, recursive, document structure-based, and LLM-based chunking. Each method has its unique benefits and
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1) Fixed-size chunking2) Semantic chunking3) Recursive chunking4) Document structure-based chunking5) LLM-based chunkingP.S. For those wanting to develop “Industry ML” expertise:SPONSOR US1 Comment
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