Below is the given Python with Machine learning code. Covid is one of the most contagious disease. In little over four months the virus destroyed the world.
In this packet i focused on covid-19. These methods can be useful to predict the risk and effects of such an epidemic. Predictions can be helpful to control and prevent the spread of disease.
I did this in Google colab juypter notebook platform. Here i installed some libraries . They are:-
The extension of Python package pycountry providing conversion functions. pycountry-convert module is built upon Python3 and has dependencies upon several Python modules available within Python packageindexpypi.
The plotly.expresss module contains functions that can be create entire figures at once.
Xgboost gradient boosting is one of the most powerful technique for building predictive model.
After applying some measures i got world wide daily case and death count. In this logarthmic scale we can see the deaths growth are increasing.
And then we can also try converted categorical to Integer for province state values to a string.