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Examining whether prior medal outcomes can predict future medal outcomes for a given country and event. This includes logistic regression and gradient boosting trees.

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Machine_Learning_in_Python

This project examines 120 years of Olympic History and Events data to better understand whether prior medal outcomes can predict future medal outcomes for a given country and event. We specifically focus on data from the 2000, 2004, 2008, and 2012 Summer Olympics to predict whether that country will obtain a medal for a specified event in 2016.

We recommend using a Gradient Boosting trees model, because it correctly predicts some events in which teams obtain a medal, compared to the Logistic model which does not.

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Examining whether prior medal outcomes can predict future medal outcomes for a given country and event. This includes logistic regression and gradient boosting trees.

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