This project aims to analyze the relationship between weather data and power production. It involves collecting weather data such as temperature, wind speed, pressure, and solar radiation, and using machine learning models to predict power production based on this data. The goal is to optimize power production efficiency by understanding how weather conditions impact it.
The main technologies used in this project are:
- Python
- Pandas
- Scikit-learn
- Matplotlib
- Seaborn
If you would like to contribute to the project, please submit a pull request. Any accepted contributions are greatly appreciated.