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This is a movie recommendation system which uses cosine-similarity. Movie data is fetched from https://www.themoviedb.org/ . Check out the backend at https://github.com/Saksham-1508/movie-recom-backend

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Pro Recommender

An awesome movies recommendation app to help you with your daily entertainment!


Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Contributing

About The Project

HomeScreen


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Built With

Following libraries/frameworks have been used in this project

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Getting Started

Install the following packages and dependencies to get started

Prerequisites

  • npm
    npm install npm@latest -g

Installation

  1. Get a free API Key at https://www.themoviedb.org/ and enter your apikey in tmdbCreds.py in the backend folder and Creds.js in /src/components/Creds.js
  2. Clone the repo
    git clone https://github.com/samay-rgb/Pro-Recommender.git
  3. Install NPM packages
    npm install
  4. Install following python libraires
    pip install sklearn pandas numpy sklearn flask flask_cors

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Usage

Browse over 16000 movies for recommendations using the subtle user interface . You can simply search for a movie or explore some trending movies as well. Currently we have only added English movies to our data. Other langauges movies will be added soon.

  • Open terminal in the cloned repo directory and run the following command
    npm start
  • In another terminal run the following commands
    cd backend
    python main.py

Trending


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Movie


Recommendations

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See the open issues for a full list of proposed features (and known issues).

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

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Contact

Saksham Yadav- Github LinkedIn- 20bcs191@iiitdmj.ac.in

Samay Sagar - Twitter LinkedIn- rahuldba99@gmail.com

Project Link: https://github.com/samay-rgb/Pro-Recommender

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About

This is a movie recommendation system which uses cosine-similarity. Movie data is fetched from https://www.themoviedb.org/ . Check out the backend at https://github.com/Saksham-1508/movie-recom-backend

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  • Jupyter Notebook 79.3%
  • JavaScript 13.6%
  • CSS 3.9%
  • Python 2.2%
  • HTML 1.0%