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🍍 🍇 Better Diet to fight Covid-19 🍌 🍉

Using Machine Learning, We try to analyze the food consumption from countries all over the world to see whether there's a relationship between given country food habits and their recovery rate.

Dataset

Data is gathered by this fantastic Kaggler Maria Ren. Data is divided into four datasets, they all have the same 170 rows, which are all countries, and same columns, which are 23 different food categories and COVID-19 statistics for each country. All four datasets share the same values of the columns of COVID-19 statistics for each country, the difference between them is explained as follows:-

  • Fat Supply Quantity Data:- for each country, it demonstrates the fat consumption percentages distributed amongst all food categories.
  • Food Supply Quantity in Kg:- for each country, it demonstrates the food supply quantity consumption percentages distributed amongst all food categories.
  • Protein Supply Quantity Data:- for each country, it demonstrates the protein consumption percentages distributed amongst all food categories.
  • Food Supply Data in Kcal:- for each country, it demonstrates the energy intake consumption percentages distributed amongst all food categories.

Full EDA is found on EDA.ipynb notebook and the modeling is on modeling.ipynb.

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  • Jupyter Notebook 99.9%
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