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Movie Pundit

Find your next flick by asking the (almost) all-knowing Movie Pundit

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About The Project

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There are many great streaming services to watch movies online in todays day and age. However, their build in content suggestion system is quite a bit broken and often times distracting, as convenient as it may be. This was the inspiration behind this Project. To iteratively build the best Movie Recommendation System that asks you what type of movie you would like to watch, no tell you what you should be watching in an intrusive way.

Why use Movie Pundit:

  • Fast and Seamless with a catalogue of 5000+ movies to boot
  • Integration with TMDB API allows you quicky read up the entire summary from IMDB itself
  • Created by movie buffs. We have painstakingly created the Content Recommendation Model from Scratch Know More »

Of course, building a recommendation system is a continuous process and requires iterative improvements and matures over time. We will be updating the model on the backend per the issues/user feedback and we aim to make the most authentic recommender on the internet!

Movie Pundit Home

Visit Movie Pundit to check it out now!

Built With

This project is made with :

Getting Started

Before you start working on this project/fork it, it is highly recommended that you check out how the model was developed here : Model ipynb

We can clone the entire project
To get a local copy up and running follow these simple example steps.

Prerequisites

This is an example of how to list things you need to use the software and how to install them.

  • pip
    python -m pip install –upgrade pip

Installation

Below is an example of how you can instruct your audience on installing and setting up your app. This template doesn’t rely on any external dependencies or services.

  1. Get a free API Key at developers.themoviedb.org/3/getting-started/authentication
  2. Clone the repo
    git clone https://github.com/KaProDes/Movie_Pundit.git
  3. Install pip packages (It is recommended to this in a venv)
    pip install requirements.txt
  4. Edit this line by entering your API key in app.py
    my_api_key = "ENTER YOUR API_KEY"
  5. Launch the Project by writing
    streamlit run app.py

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag “enhancement”.
Don’t forget to give the project a star! Thanks again!

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE.txt for more information.

Contact

Your Name – @KapProDes[email protected]

Project Link: https://github.com/KaProDes/Movie_Pundit

Acknowledgments

Special thanks to all my teachers and mentors. I have made this project as part of my Social Network Analysis and Big Data Analytics practical learning.

GitHub

GitHub - KaProDes/Movie_Pundit at pythonawesome.com
An open source movie recommendation WebApp build by movie buffs and mathematicians that uses cosine similarity on the backend. - GitHub - KaProDes/Movie_Pundit at pythonawesome.com