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Imagine we are working for the UN. We want know what countries to give the most aid to. We want to identify the countries that need the most help. Using the US as an arbitrary benchmark, we want to predict what countries have a lower life expectancy than the US based on our ML model.

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MIT-BTT-AI-Final-Project

Project Overview: Imagine we are working for a global NGO. We want know what countries to give the most aid to. We want to identify the countries that need the most help. Using the US as an arbitrary benchmark, we want to predict what countries have a lower life expectancy than the US based on our ML model.

Utilizing data from the World Happiness Report (WHR) data set, we used binary classification models to seperate countries into two categories:

  1. countries with a life expectancy lower than the US
  2. countries with a life expectancy higher or equal to the Us

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Imagine we are working for the UN. We want know what countries to give the most aid to. We want to identify the countries that need the most help. Using the US as an arbitrary benchmark, we want to predict what countries have a lower life expectancy than the US based on our ML model.

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