Training
Hands-On Workshop: Build Hybrid Search Apps with Milvus 2.5
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What will you learn?
Milvus 2.5 introduces text search by introducing native full text search capabilities, seamlessly combining term-based matching with vector similarity in a single system. This feature automatically handles text-to-vector conversion and real-time BM25 scoring, eliminating the complexity of manual embedding generation and external processing pipelines.
Topics Covered
- How to implement powerful hybrid search solutions with just raw text input
- Techniques for enhancing Retrieval-Augmented Generation (RAG) applications
- Steps to leverage BM25 scoring for improved search relevance
- Methods to combine semantic and term-based search for optimal results
Perfect for developers looking to build more accurate search applications or enhance their RAG systems while significantly reducing implementation complexity and maintenance overhead.
Meet the Speaker
Join the session for live Q&A with the speaker
Stephen Batifol
Developer Advocate
Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing.