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Music Recommender System Using Apache Spark and Python

A recommender system using Alternating Least Squares matrix factorization technique to recommend new artists to a user based on implicit feedback.

Technology Stack:

  • Spark MLlib
  • Python
  • IPython

Required Installation:

  • JDK and JRE
  • Python 2.7.x
  • Python developer dependencies - sudo aptget install pythondev
  • Pip - sudo aptget install python-pip
  • IPython - sudo pip install ipython
    sudo pip install jupyter
  • Apache Spark - wget http : //apache.arvixe.com/spark/spark-1.5.2/spark-1.5.2-bin-hadoop2.6.tgz
    tar-xzf spark-1.5.2-bin-hadoop2.6.tgz

Instructions for running:

git clone https://github.com/gsrajadh/Music-Recommender-Using-Spark.git
cd Music-Recommender-Using-Spark
IPYTHON_OPTS = "notebook" $SPARK_HOME/bin/pyspark

Dataset:

  • A modified subset of the publicly available dataset from Audioscrobbler containing 150k users