This is a project to implement Simple and Multiple Linear Regression on the same dataset that is related to Fuel Consumption and Carbon Dioxide Emission of Cars. Simple Linear Regression is a technique used to model the relationship between two numeric variables: an independent variable ( 'Fuel Consumption' in this project) and a dependent variable ( 'CO2 Emission' in this project), while in Multiple Linear Regression uses two or more independent variables. The goal is to find a linear equation that best represents the relationship between the variables so that we can make predictions based on new values of the independent variable(s).
- Read Data file.
- Explore the Data and select useful Features.
- Plot the data to find better Relationships.
- Split data into Training and Test sets.
- Create and Fit the Model with selected Feature(s).
- Plot the Output.
- Evaluate the Performance of the Model.
- scikit-learn
- pandas
- numpy
- matplotlib
Feel free to Contribute and Improve this by creating a Pull Request or an Issue.
