Skip to content

Latest commit

 

History

History
28 lines (16 loc) · 959 Bytes

README.md

File metadata and controls

28 lines (16 loc) · 959 Bytes

Unsupervised ML to Predict Covid-19 Cases and Deaths

CAPP 30254

The objective is to model the cases of COVID-19 and related deaths at the country level. Data from John Hopkins University on cases and deaths, World Bank on country data, and Oxford University on policy measures are used to train the model.

Breakdown of folders:

data: contains cleaned datasets

data: WB data: contains World Bank source data

predictions: python pickle files of predicted data

scripts: contains scripts that clean and prepare the data, train models, output predictions, visualize predictions

trained_classifiers: contains pickle files of the various trained models

visualizations: contains file output from various scripts

Instructions to run the code:

Please run the jupyter noteboooks in the following order:

  1. covid_dataset.ipynb
  2. model_fitting.ipynb
  3. MLP Classifier.ipynb
  4. Model_output.ipynb