Shiv talked to members of the group and learned about their interests. An idea was created, then slowly refined.

What it does

Gives the user an opportunity to select data sets. Then, the app provides custom inputs and outputs for the user to pick from. With the necessary data, the backend trains a network and allows the user to make predictions right from their phone!

How we built it

TensorFlow, Android Studio, and the Google Cloud Platform.

Challenges we ran into

Communication from the frontend to backend.

Accomplishments that we're proud of

How far we got without any prior knowledge or experience. Through our own fierce interest, we gained a deeper understanding of how TensorFlow computations are performed, or an opportunity to write our own database.

What we learned

Documentation is a really important aspect in this kind of project.

What's next for SKLS's AI App

Connecting the back and front ends (fixing the authentication issues we were having) and finishing the computations for our other files

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