SynthGAN

SynthGAN is a GAN based model whose objective is to create synthetic collaborative datasets.

At present it consists of three components:

1. Deep matrix factorization that is used to perform dimension reduction and generate a new dataset of emebeddings.
2. Generative Adversarial Network is intended to be a fully modular component that can be built using just two build functions; one each for the generator and discriminator components.
3. K-means Clustering is used to group together similar user, item data points.

This project is inspired by the following papers:

• Generative Adversarial Networks
• Deep matrix factorizations
• RSGAN