Deep Learning Recommender Systems

A repository to experiment building recommender systems using apache MXNet.

Repo structure

• /data directory used for storing model input data

• /libs python modules used by model training script

• ./recysys.py trains the recommender system

• ./results directory used for storing model reports and results

• ./docs: research notes etc

Running the code

1. Clone this repo and cd to root

2. Download, unzip and store the ratings data:

1. $ mkdir data

2. $ wget 'http://files.grouplens.org/datasets/movielens/ml-1m.zip'

3. $ unzip -a ml-1m.zip

4. $ mv ./ml-1m/ratings.dat ./data/

5. $ rm -rf ml-1m

6. $ rm ml-1m.zip

3. Train the model: $ python recsys.py

ToDo

• [ ] Use normal data iterators with data in memory

• [ ] Use callback functions to reproduce HR@K plots