Recommender systems built using Tensorflow 2

This repo contains implementations of various recommender systems using Tensorflow 2

Models implemented:

1. Matrix factorization
2. Neural collaborative filtering
3. Item embeddings (soon)
4. User embeddings (soon)
5. User and item embeddings combined in a feed forward Neural Network (soon)

All models are trained and evaluated using Movielens.

The purpose of this repository is not to compare the methodologies listed above but to provide examples of how they can be implemented using tensorflow 2.