/Movie-Recommender-System

The Movie Recommender System is a Python-based project that utilizes K-Nearest Neighbors algorithm to provide personalized movie recommendations to users based on their input.

Primary LanguageJupyter NotebookMIT LicenseMIT

Movie-Recommender-System

This project was made using python and HTML(FrontEnd).

The project contains 2 datasets namely movies.csv and rating.csv. It has a recommender system made using python KNN notebook which contains how the recommender system was made. The API contains a main.py file which has the api for the recommender system. templates2 contains the front end of the project which was made using HTML.

Instructions to Run

  • Install all the libraries imported in main.py
  • Open a terminal
  • Type uvicorn main:api --reload
  • (If you get error saying "uvicorn is not recognized as the name of cmdlet...) Type python -m uvicorn main:api --reload
  • In the terminal an IP address will come. Follow the link.
  • In the URL after address write "/recommendations" (as we defined it in our main.py file)
  • Enter a movie name say "Bad Boys". Click Submit and it will show you the similar movies along with their similarity score.