This project is the submission for Amazon HackOn Season 3 by Team Hackverlords from BITS Pilani, Hyderabad Campus. Our project is an Advanced Movie Recommendation System that leverages machine learning and user-generated content for personalized movie recommendations.
You can watch a detailed demonstration of our project in this Prototype Video.
- Team Name: Hackverlords
- Institution: BITS Pilani, Hyderabad Campus
For building the recommendation system, we used "The Movies Dataset" available on Kaggle. You can access the dataset here.
We used the OMDb API to fetch movie details, thumbnails, and additional information. You can find the API documentation here.
To enhance our recommendation system's accuracy, we gathered a custom scraped reviews dataset. You can download the dataset here.
All the details about our recommendation system, including how it works, its components, and the algorithms used, are provided in the documentation. You can find the documentation in the root folder of the repository.
To run our recommendation system, follow these steps:
- Create a virtual environment.
- Install the necessary libraries from
requirements.txt. - Run the
main.pyfile usinguvicorn main:main_app. - To run the frontend, navigate to the
frontendfolder. - Run
npm install --forceto install frontend dependencies. - Run
npm run startto start the frontend.