LuluW8071 / Content-Filtering

Movie Recommendation using Content Filtering (Cosine Similarity) with Flask web application

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Movie Recommendation

Demo GIF

Dependencies

To install the required Python packages you can use the following command:

pip install -r requirements.txt
  • Run model.ipynb & dataset.ipynb

  • Edit api.py

    • Create an account at Algolia
    • Create your index and upload records of movies_dataset.csv
    • Create an account at TMDb
    • Get your API and edit on api.py

    # TMDB API Key Auth
    TMDB_API_KEY = '_______________' 
    
    # Algolia API Search
    
    ALGOLIA_APP_ID = '____________'
    ALGOLIA_API_KEY = '______________________'
    ALGOLIA_INDEX_NAME = '_______________________'
    

    Note:
    Run py api.py with Test Cases 1 & 2 to check request

  • Run app.py To run the app.py, load the dependecies requirements, edit api.py and use the following command:

    py app.py
    

✨ Enjoy the demo


Feel free to send issues if you face any problem.
✨ Don't forget to star the repo :)

About

Movie Recommendation using Content Filtering (Cosine Similarity) with Flask web application

License:MIT License


Languages

Language:Jupyter Notebook 64.4%Language:HTML 12.4%Language:CSS 11.8%Language:Python 6.1%Language:SCSS 3.6%Language:JavaScript 1.8%