Pyrates

This project was inspired by the ongoing fight against piracy across the world.

This program achieves the primary function of educating users (particularly seafarers) of the dangers of piracy. It provides many ways of breaking down and visualizing historical data about pirate attacks, and helps users understand trends. In an effort to help users sail safely, there is also a piracy predictor beta, which given a coordinate pair, assigns a number value to how at risk a ship at that location is for piracy.

We built this project using a Streamlit front end and a scikit backend for the prediction model portion, the app was then deployed on the Streamlit cloud so it can be accessed through a browser

The prediction model turned out to be really difficult, our data set was a multi-tabled datasheet which was hard to reconcile. Additionally, picking an ML library to agree with our data set and give us the results we wanted in the short time frame we had.

We're proud of the finished project, that we were able to come up with a working app in such a short time. We're proud specifically of our map displays and our ML prediction model.

We learned that prediction modeling is extremely data specific, and very hard to get to work. We also used how to use and deploy stream lit, and stay organized and synchronized as multiple people worked on the same code.

Built With

• python
• scikit
• streamlit