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A repository to experiment building state of the art recommender systems using apache MXNet

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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

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A repository to experiment building state of the art recommender systems using apache MXNet

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