Moodify

Inspiration

We were inspired when listening to music from the hackathon and thought of being able to listen to similar music

What it does

It takes a given song as an mp3 file and predicts its mood, then provides recommendations to similar songs based on the mood

How we built it

We used python to generate a model using training data from MTG Jamendo's dataset. Our front end uses html/css.

Challenges we ran into

The most challenging part of this project was creating the AI model as none of us had extensive experience with AI. Also used Flask for the first time and so had a challenging time integrating it.

Accomplishments that we're proud of

We are proud of being able to create an AI model for the first time.

What we learned

We learned how to create an AI model and work with data sets. USed Flask to integrate the backend with the frontend.

What's next for Moodify

We will continue to improve our AI model to provide better predictions and recommendations. We also hope to be able to integrate with Spotify, Apple Music, or another music app

Built With

• css
• flask
• html
• javascript
• machine-learning
• python
• scikit-learn