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Movie Recommendation using Matrix Factorisation, User based collaborative and Item based collaborative filtering

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Movie-recommendation

The data set have been taken from movieLens and the movie information was extracted from IMDB.

Getting Started

cd into any of the heroku directories

cd heroku

pip install all the requirements using

pip install requirements.txt

Run the flask app

python app.py

File Description

This has been deployed but is not working due to some server load issue but will work in localhost The ratings in the app should be an integer ranging from 0-5

Deployment

The deployment of these apps has been done through Heroku
The database was stored using Mlab

Movie Lens Dataset Description

The small version of this dataset have been used which contains 100,000 ratings and 3,600 tag applications applied to 9,000 movies by 600 users.
Only ~800 movies were used from this dataset due to server issues.
We have used 3 files from this dataset

  • ratings.csv - Each line of this file after the header row represents one rating of one movie by one user
  • movies.csv - Each line of this file after the header row represents one movie
  • links.csv - Each line of this file after the header row represents one movie