The Weather Prediction Project is a machine learning-based solution designed to forecast weather conditions, focusing primarily on predicting average temperatures. Leveraging historical weather data, this project utilizes a Random Forest Regressor model, among other advanced machine learning techniques, to provide accurate and reliable temperature forecasts.
- Data Preprocessing: Implements comprehensive data cleaning and preparation processes to ensure high-quality input for model training.
- Advanced Modeling: Utilizes RandomForestRegressor for forecasting, with infrastructure in place for easy experimentation with other models.
- Model Evaluation: Employs Mean Absolute Error (MAE) for assessing model performance, ensuring predictions are both accurate and practical.
- Modular Design: Project structured for easy maintenance and scalability, facilitating enhancements like adding new prediction features or integrating different models.
- Easy Installation: Includes a batch file for quick setup of all required libraries, streamlining the initial setup process for all users.
To get started with the Weather Prediction Project, clone this repository and follow the setup instructions below.
- Python 3.x
- pip
Run the install_dependencies.bat file to install all the necessary Python libraries:
install_dependencies.bat