/matrix-factorization

Applications of matrix factorization using GLRM

Primary LanguageJupyter Notebook

Matrix factorization for recommendations

For introduction to matrix factorization in context of recommender systems see this piece from IEEE.

Probabilistic interpretation of penalty in matrix factorization can be found in Probabilistic Matrix Factorization.

Here you can find the original GLRM paper.

Requirements

The project requires the following Python packages (I've checked with 3.5)

  • jupyter-notebook
  • numpy
  • pandas
  • seaborn
  • h2o

Note that first four packages are available in Anaconda by default.

Usage

See Makefile for loading and preparing data. For actual interesting stuff see notebooks folder.