What did the different teams at the Red Cross Hackathon do

What did the different teams at the Red Cross Hackathon do

On the 20th of May DataMission organised a hackathon for the Red Cross and 510.global. The day is described here. This blogposting contains more technical details of what the teams did.

Machine Learning model teams

The first team, team015, tried to tweak the inputs and to combine them to thus find a better input for the prediction model. This is called feature engineering. They used RandomForest and Negative Binomial Logistic Regression algorithms. While the data only contained the number of partially damaged and the number of completely damaged houses, they decided to focus on the total number of damaged houses too. While their model was doing very well on the test data, it had an R-squared score of 0.21 on the real data set. Read more about What did the different teams at the Red Cross Hackathon do

Predicting typhoons and visualising their impact for Red Cross

Predicting typhoons and visualising their impact for Red Cross

[:en]As technology grows and becomes more and more a part of everyday life, we are starting to truly understand how to utilize it for the good of society.  Using data for social change is a relatively new trend.  However, it is picking up steam and many organizations are looking into new innovative ways to use this valuable tool for the greater good of humanity. Read more about Predicting typhoons and visualising their impact for Red Cross