Epidemic Predictor

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  Example Usage

Inspiration

This project was developed in 2020, during the worst global health and economic crisis in 70 years: COVID-19. This package dedicated to all essential workers for their sacrifices. We are deeply sorry to every who got sick, and worse, passed away by this virus.

What it does

This package uses machine learning to predict when will the next epidemic happen. So people can prepare earlier.

How I built it

I built it using python scikit-learn, a machine learning module to train the model able to take in population, democracy index, poverty, GDP, life expectancy, global health spending per GDP, and flights. With historical data, then it will give a percentage of whether will an epidemic happening in that given year or not.

Challenges I ran into

The most significant challenge is to get the training dataset. Since this is a brand new idea, there's no available training set. It takes me quite a long time to find all the different parameters. And I create a python script that able to generate a CSV file with all parameters and does an epidemic happen that year.

Accomplishments that I'm proud of

The accomplishment that I'm proud of is to train the machine learning model and research the similarity between each "epidemic" year.

What I learned

I learned how to use machine learning using scikit-learn to train the model. And collect the data.

What's next for Epidemic Predictor

The next for Epidemic Predictor will be adding more features and more correctness and accuracy.

Built With

• flask
• pip
• python