Is She Mad At Me? (ISMAM)

Inspiration

We are all single male college students who do not understand female interaction. Therefore, we created an app to help us in our romantic endeavors.

What it does

Uses Machine-Learning to analyze text messages for the emotions of the sender.

How we built it

We used Co:here's text classification model and trained it using our own dataset.

Challenges we ran into

Integrating our front-end (Chrome extension) with our back-end (Co:Here model in JavaScript).

Accomplishments that we're proud of

Trained a Machine-Learning model with reasonable accuracy and creating a chrome extension.

What we learned

It is difficult to find data for Machine-Learning models and integrating back-ends with front-ends can be difficult as well.

What's next for Is She Mad At Me?

Increase the quantity and quality of the data-set to produce more accurate results.

Built With

• chrome
• co:here
• css
• html
• javascript