Car Price Prediction System Using Machine Learning

Description

Car Price Prediction System using Machine Learning (Python – Full Working Project)

If you are a final year student looking for a real-world Machine Learning project that is practical, trending, and easy to explain in viva, this Car Price Prediction System is the perfect choice.

This project predicts the resale value of used cars using advanced Machine Learning algorithms based on features like brand, model, year, fuel type, transmission, owner type, and kilometers driven.

🚀 Why This Project is Special?

• ✔ Real-world problem-solving project
• ✔ Professional folder structure
• ✔ Fully commented and clean code
• ✔ Model training + evaluation included
• ✔ Streamlit-based interactive web application
• ✔ Ready-to-run ZIP package
• ✔ Suitable for BCA / MCA / B.Tech / M.Tech / Data Science

💻 Project Features

• Car detail input form (UI-based prediction)
• Data preprocessing and feature engineering
• Random Forest Regression model
• Performance metrics (R², MAE, RMSE)
• Model saving using Joblib
• Retraining option with custom dataset
• Training report generation (JSON)
• Deployment-ready architecture

🛠 Tech Stack Used

• Python
• Pandas & NumPy
• Scikit-learn
• Joblib
• Streamlit (Web App UI)

📦 What You Will Get

• ✅ Complete Source Code (Professional Structure)
• ✅ Ready-to-run Streamlit Web App
• ✅ Trained ML Model File
• ✅ Sample Dataset (CSV)
• ✅ Training & Testing Pipeline
• ✅ Setup Instructions (README)
• ✅ Project Report (DOC Format)
• ✅ PPT Presentation
• ✅ Viva Questions with Answers

This is not just a basic notebook project. It includes a proper ML pipeline, model saving, evaluation metrics, and a working UI for demonstration. You can confidently present this project in your final year submission and even use it in interviews.