https://www.youtube.com/watch?v=YYdt8L52VrA&t=24s
https://gauravamohan.medium.com/sf-event-recommender-using-llms-d1f9e898fd
- looks for themes in events using transformer models to potentially be used as a feature in embeddings
- combines all the scraped events and reformats to standardize features and emebeddings for models
- similarity search on event embeddings and user embeddings and storing it in mysql database
- node.js file for backend to push mysql data to the front end. Dynamically takes liked events and calls update_recs to update table
- factors liked events into similarity search to tune recommendations to user's liked events.