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Project on university- making a recommendation system using Clustering and Association Rules

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MovieLens-recommendation-system

Project description

Group name: The Miners Participants:

  1. Lidia Wiśniewska - Code Repository
  2. Wiktoria Szarzyńska - Code Repository
  3. Joanna Szczublińska - Project Poster
  4. Maria Musiał - Project Report

Dataset name: MovieLens

link to our dataset: from here

Project structure:

Our main goal is to create a recommendation system based on the MovieLens dataset using clustering and association rules. To reproduce the project simply run the jupyter notebook file: main.ipynb.

The report is available in MovieLens_report.pdf.

Inside the code folder, you can find the following files:

  • recommendation.py - the main file with the used functions
  • main.ipynb - reproducible set of samples presented in Jupyter Notebook
  • testing.ipynb - set of tests of the recommendation.py file
  • ratings.csv and movies.csv datasets used in the assignmnet

How to use the code

Whole project is created in jupyter notebook which uses functions written in python in recommendation.py file. We load our data in the first place ysing pandas library. This is crucial to continue the creation of recommendation system. To provide the same experiment: download the files mentioned in the repository and also dataset from here.

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Project on university- making a recommendation system using Clustering and Association Rules

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