"Chunking Techniques for RAG and LLMs: A Guide"

The way you chunk your data can make or break performance. From Fixed Size and Recursive Chunking to Semantic, LLM-based, and even Late Chunking—each technique has its own strengths and tradeoffs. Knowing when to use which can drastically improve retrieval accuracy and efficiency. We broke down the major approaches: ✅ Fixed Size Chunking ✅ Recursive Chunking ✅ Document-Based Chunking ✅ Semantic Chunking ✅ LLM-Based Chunking ✅ Late Chunking If you’re working with RAG systems or search-augmented LLMs, this is your go-to guide. 💡 Bonus: We’re offering a Free GenAI Program to help you deepen your expertise. Don’t miss it 👉 https://lnkd.in/dfhwme-A #AnalyticsVidhya #GenAI #Chunking