Training
Tutorial: Building a Semantic Text Search Application
Zilliz Webinar - Zoom
Join the Webinar
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What will you learn?
In this hands-on tutorial, we’ll introduce embeddings and vector search from both an ML- and application-level perspective. We’ll start with a high-level overview of embeddings and discuss best practices around embedding generation and usage.
Then we’ll use this knowledge to build a semantic text search application. Finally, we’ll see how we can put our application into production using Milvus, the world’s most popular open-source vector database.
What you’ll need:
- Python 3.9 or above
- A basic understanding of vectors and databases
What you’ll learn:
- What is vector database
- What is semantic similarity
- How to use a vector database to find similar texts
Meet the Speaker
Join the session for live Q&A with the speaker
Yujian Tang
Developer Advocate at Zilliz
Yujian Tang is a Developer Advocate at Zilliz. He has a background as a software engineer working on AutoML at Amazon. Yujian studied Computer Science, Statistics, and Neuroscience with research papers published to conferences including IEEE Big Data. He enjoys drinking bubble tea, spending time with family, and being near water.