From Queries to Pints: Building a Beer Recommendation System with pgvector

Discover how easily you can create a recommendation system from scratch using modern AI and database technologies.

In this session, we’ll build a beer recommendation system using advanced language models and PostgreSQL's pgvector extension. By leveraging the capabilities of pgvector, we can seamlessly store high-dimensional embeddings generated from beer descriptions and perform similarity search with user preferences.

Whether you're a seasoned database administrator or just starting to explore the potential of AI, this presentation will equip you with practical insights and hands-on techniques to integrate machine learning into your database workflows. Join to learn how to turn complex data into intuitive recommendations! No prior ML knowledge required.

Links to projects used in this talk: PostgreSQL, pgvector extension, all-MiniLM-L6-v2 model, beer dataset