🚗 Car Price Prediction Web App 💰

An end-to-end Machine Learning web application that predicts the price of a used car based on key features such as brand, model, fuel type, year of purchase, and kilometers driven. The project demonstrates the complete ML workflow — from data preprocessing to model deployment using Flask.

✨ Features

📊 Data cleaning & exploratory data analysis

🤖 Machine Learning model training using Linear Regression

💾 Model saving and loading using Pickle <.pkl>

🌐 Flask-based backend for real-time predictions

🎨 Simple, clean, and responsive HTML + CSS UI

⚡ Instant car price prediction

🧠 Tech Stack

Programming Language: Python

Libraries: Pandas, NumPy, Scikit-learn

Model: Linear Regression

Backend: Flask

Frontend: HTML, CSS

Development Tools: Jupyter Notebook

📥 Input Parameters

The model predicts car prices based on:

Car Company & Model

Year of Purchase

Fuel Type

Kilometers Driven