Distributed Computer Protocol Challenge

What it does

Predicts the daily COVID infection rate

How we built it

Built inside of the jupyter notebook environment using pandas, numpy, plotly and seaborn to visualize the data and fbprophet to make predictions

Challenges we ran into

When we ran the base model, no hyperparameters, we ran into extremely high MSE's (+50k). After testing and more data exploration, eventually found out we needed to include seasonality into the prediction.

Accomplishments that we're proud of

For two of us this is our first hackathon and another two of us have little to no coding experience so completing one challenge is a huge milestone for us!

What we learned

Practiced fbprophet and time series prediction in the challenge but overall, learned about API application, code deployment and reactJS

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Loblaw Challenge #1

What is it

Came up with a concept to use computer vision for in-store customer tracking and also for inventory management

Challenges

The team had to properly research how computer vision worked in order to come up with a viable use in the retail industry

What we learned

We learned about how computer vision works and what the industry is doing currently to try and implement it into everyday use for the benefit of the company and consumer