This repository contains code and resources for a CO2 Emission Project that predicts CO2 emissions using Machine Learning techniques, particularly Linear Regression. The project aims to understand and predict CO2 emissions based on various input features.
The CO2 Emission Project utilizes Machine Learning to predict CO2 emissions based on factors such as vehicle characteristics, engine specifications, and other relevant features. By employing Linear Regression, the project aims to build a predictive model that can estimate CO2 emissions accurately.
To use the project, follow these steps:
- Clone the repository to your local machine:
git clone https://github.com/vijaymakkad/CO2-Emission-Project.git- Navigate to the project directory:
cd CO2-Emission-Project- Install the required dependencies. It's recommended to set up a virtual environment before installing dependencies.
pip install -r requirements.txt- Run the main script to train the Linear Regression model and make predictions:
python main.pyThe dataset used for this project contains information about vehicles and their corresponding CO2 emissions. It includes features such as vehicle make, model, engine size, fuel type, and more. The dataset is stored in the data directory.
data/: Contains the dataset used for training and testing the model.models/: Stores trained models.utils/: Contains utility functions used throughout the project.main.py: Main script for training the model and making predictions.requirements.txt: Lists all Python dependencies required for the project.
Contributions to the project are welcome! If you have any ideas, enhancements, or bug fixes, feel free to open an issue or submit a pull request.
This project is licensed under the MIT License. See the LICENSE file for details.
For any questions or feedback regarding the project, feel free to contact Your Name.
Thank you for your interest in the CO2 Emission Project!
Below is the UI design
