BigData-on-the-spread-of-COVID-19-in-the-world

Nowadays, there is a lot of open data about the spread of COVID-19 in the world. However, few tools are presented to predict and visualize these processes. This project will show how you can download data from open sources, perform preliminary data analysis, transform and clear data, and perform predictions using machine learning models using python 3 and Jupyter notebooks.

Next, we will consider 2 different mathematical approaches to the calculation of a forecast based on linear regression.

To do this, the division of the DataSet into training and test sets will be demonstrated. It will be shown how to build models using 2 different frameworks. Then we will build a forecast and analyze the accuracy and adequacy of the obtained models.

At the end of the project, we will visualize the dynamics of COVID-19 infection spread on interactive maps.