- Why use PopcornPicks?
- Project Documentation
- Project Presentation Video
- Brief Overview of Project
- Core Applications of the Project
- Improvements Made in the Project
- TechStack Used for the Development of Project
- Steps for Execution
- Future Scope
- Contribute
- Team Members
- Contact
- License
PopcornPicks: Your movie recommender! Input movies, get tailored suggestions, and share via email. Elevate your movie choices effortlessly!
- Efficient: Lightning-fast recommendations for movie buffs! 🚀
- Adaptable: Tailor the recommendations to your taste.
- Accessible: Works across all platforms and shells.
- Insightful: Get movie insights at a glance.
- Comprehensive: Supports a wide array of user-preferred movies.
- Simple: Easy installation and setup – start discovering great movies in no time!"
Checkout for project documentation at our wiki page
You can see the project presentation at - https://youtu.be/ymAo_zXfZ0c
PopcornPicks is a user-friendly movie recommender that curates a tailored list of 10 movie predictions based on user-provided movie preferences. Users can input their favorite movies, and our algorithm refines recommendations based on feedback—Liked, Disliked, or Yet To Watch. Additionally, PopcornPicks offers the convenience of emailing the recommended movies, enhancing the movie-watching experience. For the system architecture and other details, please refer to our wiki page
The user selects upto 5 movies to get a tailored watchlist and provide feedback for the same
The user sends his/her movies feedback via an email (Notify Me button)
Check out the significant changes that we made for Project 2 here
Step 1: Git Clone the Repository
git clone https://github.com/adipai/PopcornPicks.git
(OR) Download the .zip file on your local machine from the following link
https://github.com/adipai/PopcornPicks
Step 2: Follow the setup instructions in the wiki documentation
https://github.com/adipai/PopcornPicks/wiki/Installation-and-setup
Finally, start enjoying personalized movie recommendations!
PopcornPicks is a dynamic project with endless possibilities for expansion and enhancement. Here are some exciting avenues for future development:
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User Profiles and Preferences: Implement user profiles where users can save their preferences, ratings, and watch history for a more personalized movie discovery experience.
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Integration with Streaming Services: Integrate with popular streaming services to provide real-time availability information and seamless access to recommended movies.
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Movie Reviews and Ratings: Allow users to write and read movie reviews and ratings, fostering a community of film critics and enthusiasts.
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Improved Recommendation Algorithm: Enhance the recommendation engine with more advanced machine learning models and collaborative filtering techniques to provide even more accurate and personalized movie suggestions.
The future of PopcornPicks is full of potential, and we invite developers, movie lovers, and anyone passionate about cinema to join us in making this platform the ultimate movie companion.
Please refer to the CONTRIBUTING.md if you want to contribute to the PopcornPicks source code. Follow all the guidelines mentioned in the same and raise a pull request, we would love to look at it ❤️❤️!
Aditya Pai Brahmavar
Ananya Mantravadi
Rishi Singhal
Samarth Shetty
In case of any issues, please e-mail your queries to [email protected] or raise an issue on this repository.
Contribute to the project and help us improve recommendations. Share your experience and film discoveries with us. Together, let's make PopcornPicks the ultimate movie companion! PopcornPicks is more than just code; it's a passion for cinema, and we invite you to be a part of this exciting journey. Start exploring, sharing, and discovering movies like never before with PopcornPicks! Let's make movie nights extraordinary together!
This project is under the MIT License.