This repository contains a project that explores various regression models to predict the selling price of cars based on multiple features such as mileage, fuel type, transmission type, and number of previous owners.
Data preprocessing and exploratory data analysis (EDA) for understanding car price factors. Implements Linear Regression, Ridge Regression, and Lasso Regression for predictive modeling. Feature selection and engineering to optimize model performance. Uses Matplotlib, Seaborn, and Plotly for data visualization.