We wanted to use machine learning to predict the priority of GitHub issues
What it does
How we built it
We built the model using the scikit-learn library and term frequency–inverse document frequency
Challenges we ran into
It was very difficult to query the data just due to the convoluted way it was stored.
Accomplishments that we're proud of
We're proud that our model ended up doing significantly better than a random guess.