The Weather Prediction Model is a project developed to predict weather conditions based on several input parameters such as precipitation, maximum temperature, minimum temperature, and wind speed. This model utilizes Random Forest (RF) algorithm for making predictions.
The data used for training and testing the model is sourced from Kaggle. We would like to extend our gratitude to the contributors of this dataset for making it publicly available.
- HTML
- CSS
- Python
- Flask
- Random Forest (RF)
To run this project locally, ensure you have Python installed on your system. You can install the required Python packages by running the following command:
pip install -r requirements.txt
- Clone this repository to your local machine.
- Navigate to the project directory.
- Install the required packages as mentioned above.
- Run the Flask application by executing the following command: python app.py
- Once the server is running, you can access the application in your web browser by visiting
http://localhost:5000.
We welcome contributions from the community to enhance the functionality and reliability of this project. If you'd like to contribute, please follow these guidelines:
- Fork the repository.
- Create a new branch for your feature or bug fix.
- Make your changes and ensure they are well-documented.
- Test your changes thoroughly.
- Submit a pull request with a clear description of your changes.
This project is licensed under the MIT License.
If you have any questions or suggestions regarding this project, feel free to contact us at your.email@example.com.