Recently launched my first end-to-end ML app! A film recommender system based on matrix factorization, built for Letterboxd users.

• matrix-factorization

  1 19 2.9 Python

  Library for matrix factorization for recommender systems using collaborative filtering

I originally tried using RiverML, which is dedicated to online ML, but after a ton of tweaking I still wasn't satisfied. In the end, I used the matrix-factorization library, which is not at all flashy but worked much, much better. By adjusting the learning rate and epochs for feeding new ratings into the model I can adjust how "personalized" the ratings are, and after a few days of messing with it I got it where I wanted it.

• fastapi

  470 71,223 9.8 Python

  FastAPI framework, high performance, easy to learn, fast to code, ready for production

This project is built with Streamlit for the front-end, FastAPI for the back-end and both are in Docker containers being run on AWS ECS.

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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