MovieMate

Inspiration

We wanted to create an app that helps users discover movies tailored to their tastes, while also providing additional features like trending recommendations, personalized lists, and social interaction. The goal was to simplify decision-making for movie enthusiasts and bring movie lovers together on one platform.

What it does

Personalized Recommendations: Based on user preferences, time, and ratings.

How we built it

Frontend: NextJs, React. Backend: Python, Flask. We used Google collab for training and testing Model, and preprocessing the data. and used Github for collaboration.

Challenges we ran into

Data Preprocessing: We had to tackle problems such as null values we had to clean the data remove outliers, Since we did web scraping for collection of data it was time consuming.

Accomplishments that we're proud of

We Successfully created a Movie Recommendation website by considering Genres , Time and Rating, Which helps give a more accurate result.

What we learned

The importance of user feedback in refining both design and functionality. We learned to collaborate as a team. We learned new concepts such as ML, Web Scraping and etc.