Car Price Predictor using Python

Car Price Predictor Using Python

Introduction

Car prices fluctuate due to various factors, including brand, model, condition, mileage, fuel type, and transmission. In Belarus, understanding these factors can help buyers and sellers make informed decisions. This project aims to predict car prices in Belarus using machine learning techniques, leveraging a dataset with 56,244 records and 12 key features.

Project Overview

The Car Price Prediction project utilizes a dataset containing crucial car features such as:

✅ Make & Model – Identifies the car manufacturer and model.
✅ Year of Production – Indicates the manufacturing year.
✅ Condition – Represents the condition at the time of sale.
✅ Mileage – The number of kilometers driven.
✅ Fuel Type – Includes petrol, diesel, and electric.
✅ Engine Volume – Measured in cubic centimeters (cm³).
✅ Transmission Type – Automatic or manual.
✅ Drive Unit – Includes front-wheel, rear-wheel, and all-wheel drive.
✅ Segment – Classifies cars into economic, luxury, and specialty categories.

Key Findings from Data Analysis

📌 Car prices surged significantly after the year 2000.
📌 Petrol cars with automatic transmission tend to be more expensive than diesel cars with manual transmission.
📌 Electric cars are the most expensive vehicle category.
📌 All-wheel drive cars have the highest prices compared to other drive types.
📌 Luxury and specialty segment cars command premium prices, especially European and American models.

Predictive Modeling Approach

To predict car prices, a Decision Tree Regressor was employed. This model is effective in capturing non-linear relationships and feature importance within the dataset.

🔹 Model Accuracy: 85.29%
🔹 Most Influential Factors:

• Year of Production – Newer cars typically have higher prices.
• Engine Volume – Larger engines contribute to higher price points.

Impact of This Project

🚗 For Buyers – Helps in identifying fair prices for vehicles based on their features.
🚙 For Sellers – Assists in setting competitive prices in the Belarusian car market.
📊 For Dealers – Provides insights into pricing trends for better inventory management.

By leveraging machine learning and data-driven insights, this project provides accurate car price predictions for the Belarusian automotive market. With an 85.29% accuracy rate, it serves as a valuable tool for anyone looking to buy or sell a car in Belarus.