Introduction:

Carbon emissions and environmental protection issues have brought pressure from the international community during Chinese economic development. Recently, Chinese Government announced that carbon emissions per unit of GDP would fall by 60–65% compared with 2005 and non-fossil fuel energy would account for 20% of primary energy consumption by 2030.The Beijing-Tianjin-Hebei region is an important regional energy consumption center in China, and its energy structure is typically coal-based which is similar to the whole country.

Therefore, forecasting energy consumption related to carbon emissions is of great significance to emissions reduction and upgrading of energy supply in the Beijing-Tianjin-Hebei region. Thus, this study thoroughly analyzed the main energy sources of carbon emissions including coal, petrol, natural gas, and coal power in this region.

Solution Requirement:

A Machine Learning Model for calculating CO2 emission by country, Due to the increasingly deteriorating environment, it is time the government to upgrade the energy consumption structure.

Install required packages and libraries.

To complete the project, you need the following packages and libraries.

Anaconda Navigator

Jupyter

Numpy

Pandas

Matplotlib

Scikit-Learn