Forest Fire Data link: FWI prediction
This project aims to develop a machine learning model to predict weather conditions in forests. This could be useful for forest management, fire prevention, and other applications.
The project will use a variety of data sources, including historical weather data, satellite imagery, and ground-based sensors. The data will be cleaned and preprocessed, and then used to train a machine learning model. The model will be evaluated on its ability to predict weather conditions on a held-out test set.
Once the model is trained and evaluated, it will be deployed to a production environment. This could involve integrating the model with a web service or mobile app.
- Python 3
- NumPy
- Pandas
- Scikit-learn
- Matplotlib
To install the required Python packages, run the following command:
pip install -r requirements.txt
To train the machine learning model, run the following command:
python train_model.py
To predict weather conditions, run the following command:
python predict.py
The following is an example of the output of the predict.py script:
Predicted weather conditions:
Temperature: 25 degrees Celsius
Humidity: 75%
Precipitation: 10%
Wind speed: 5 m/s
We welcome contributions to this project. Please feel free to open an issue or pull request if you have any suggestions or bug fixes.