Inspiration
Our team was trying to figure out how to improve one's mental and physical help through a A.I. which helps determine the best playlist for your mood.
What it does
MeloMood is a friendly and engaging app designed to help users check in on their feelings and discover personalized music that matches their mood. The app combines mental wellness with music enjoyment, creating a supportive community experience.
How we built it
We used machine learning with cosine similarity to create an AI model that would recommend you 10 random songs based on your emotion (for example, happy, sad, or anxious). We used flask and python with numpy, pandas, sklearn, and various other libraries for the backend. We also used SQLite for the database in the backend. For the frontend, we just used HTML/CSS/JS.
Challenges we ran into
Having to A.I., we needed to learn languages compatible with flask and web design. A lot of new things were new to us, and we had technical difficulties with trying to use VSCode to collaborate together.
Accomplishments that we're proud of
We are proud not losing our composure the whole time we were coding. We are also proud of finally having finished the project and having learned so many skills along the way.
What we learned
We learned various data analysis, Flask, and web development skills as well as the whole process of trying to connect to an API. None of us were at all familiar with AI at the start of the competition, but we learned along the way and now we understand the basics.
What's next for Melo Mood
The next step for Melo Mood would be to implement more mental health features like recommending a other activities, not just music, based on the emotion the user says.
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