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Course Recommendation System

Submitted by:

  • IMT2020001 - Srinivas Manda
  • IMT2020003 - Karanjit Saha
  • IMT2020084 - Arya Kondawar
  • IMT2020502 - Monjoy Narayan Choudhury

Files Submitted

Inside the zip following files are present:

  • Readme.md : This readme file.
  • Presentation.pdf: The presentation file used for the oral presentations.
  • Code: A folder that consist of:
    • Colaborative Filtering.ipynb: A jupyter notebook where colaborative filtering user based is implemented.
    • KMeans.py: is the python file that contains our KMeans implementation to be used by the other notebooks
    • SVD.py: is the python file that contains our SVD and reduced SVD implementation to be used by the other notebooks
    • Course Recommendation System.xlsx: The dataset
    • mainWithMean.ipynb: This implements approach 1 in presentation with NaNs replaced as mean of the subject.
    • main_SVD_KMeans.ipynb: This implements SVD followed by KMeans(approach 2).
    • Notebooks: Consist of jupyter notebooks for various trials we tried to do. These notebooks are mostly to play around and verify our results with sklearn KMeans and SVD. Also consist of the notebook used to the initial Exploratory Data Analysis (EDA.ipynb)

Instructions to run

User must have a valid jupyter notebook setups and environment setup. Other than that one must have pandas, numpy installed as a bare minimum.