Machine learning on energy consumption

Overview

The study focuses on the development of a machine learning model for forecasting the energy needs of Greece, while evaluating the adoption of the renewable energy sources, electricity demand and carbon emissions. Using the "International Energy Statistics" dataset from Kaggle, the analysis includes a comparative overview of energy trends at a global level, including a comparative overview of energy trends at a global level. level and especially in the G10 countries and the Balkans. The findings highlight the importance of technological developments, government policies and economic factors in the promotion of renewable energy sources. To forecast energy needs, the Scikit-learn library was used, with with emphasis on linear regression and other algorithms. Although the original results showed a high deviation from the actual values, the study suggests the importance of improving the models and incorporating additional data. Overall, the research supports strategic energy planning, environmental planning, and environmental management. environmental sustainability and energy security, providing valuable information on the future energy needs of Greece.