Skip to content

Marco-metric coronavirus model to predict the number of confirmed cases in different regions around the world.

Notifications You must be signed in to change notification settings

jacob-evarts/coronavirus-prediction

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation


A Macro-Metric Machine Learning Prediction for CoronaVirus Propagation

  

Requirements

  1. Python3
  2. Pip3
  3. Python3 Numpy
  4. Python3 Pandas
  5. Python3 Matplotlib
  6. Python3 SciKit-Learn

(Note: These requirements are fulfilled by following Setup)

Setup

  1. $ git clone https://github.com/jacobian0208/Coronavirus.git
  2. $ cd CoronaVirusMLPrediction
  3. $ bash setup.sh

Files & Directories

corona_virus.py
Our main script with finely tuned hyperparameters that optimize the accuracy of all future CoronaVirus regional predictions.

setup.sh
Responsible for setting up the user space required for running corona_virus.py.

Datasets
Directory filled with CSV styled data which was used to train and tune the hyperparameters of corona_virus.py. We found covid_19_data.csv to be most helpful.

All personal user space tests were ran and confirmed to work on the CloudLab profile ConTools/n-Ubuntu: https://www.cloudlab.us/p/5dcc9f6c-3f8a-11e9-910b-e4434b2381fc.

Collaborator: Nolan Ruldoph

About

Marco-metric coronavirus model to predict the number of confirmed cases in different regions around the world.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published