https://github.com/priteshsurale/used_car_price_detection
🚗 Car Price Detection is an experimental machine learning project that predicts the optimal price for buying or selling used cars. Built with PyTorch, the model uses three key features: Car Accident History, Age of the Car (in years), Mileage (in kilometers/miles)
https://github.com/priteshsurale/used_car_price_detection
aritificial-intelligence price-prediction python3 pytorch-implementation
Last synced: 6 months ago
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🚗 Car Price Detection is an experimental machine learning project that predicts the optimal price for buying or selling used cars. Built with PyTorch, the model uses three key features: Car Accident History, Age of the Car (in years), Mileage (in kilometers/miles)
- Host: GitHub
- URL: https://github.com/priteshsurale/used_car_price_detection
- Owner: Priteshsurale
- Created: 2025-02-14T05:06:36.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2025-03-26T07:13:05.000Z (7 months ago)
- Last Synced: 2025-03-26T07:31:38.847Z (7 months ago)
- Topics: aritificial-intelligence, price-prediction, python3, pytorch-implementation
- Language: Jupyter Notebook
- Homepage:
- Size: 605 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🚗 Car Price Detection
  
## 📌 Overview
Car Price Detection is an experimental machine learning project designed to predict the best price for buying or selling used cars. The model is built using PyTorch and takes three input features to make predictions:
1. **Car Accident History** (`0` for accident history, `1` for accident-free)
2. **Age of the Car** (in years)
3. **Mileage** (in kilometers/miles)
Based on these inputs, the model predicts a reasonable price for the car. This project is intended for learning and experimental purposes only. 🚀
---
## 🏗️ Project Structure
```
.
├── data
│ └── used_cars.csv # Dataset
├── model
│ ├── model.pt # Trained model weights
│ ├── x_mean.pt # Standardization parameters for input
│ ├── x_std.pt # Standardization parameters for input
│ ├── y_mean.pt # Standardization parameters for output
│ └── y_std.pt # Standardization parameters for output
├── README.md # Project documentation
├── requirements.txt # Dependencies
├── train_model.py # Training script to generate tensors
└── used_car_price_prediction.py # Script to use trained model for prediction
```
---
## 🔧 Installation & Setup
### 1️⃣ Clone the Repository
```bash
git clone https://github.com/yourusername/car_price_detection.git
cd car_price_detection
```
### 2️⃣ Install Dependencies
Make sure you have Python installed, then install required packages:
```bash
pip install -r requirements.txt
```
### 3️⃣ Train the Model (First-time Only)
Run the following command to train the model and save necessary tensors:
```bash
python train_model.py
```
### 4️⃣ Run the Prediction Script
Once the model is trained, use the prediction script:
```bash
python used_car_price_prediction.py
```
---
## 🧠 Model Training
The model is trained on a dataset of **used cars**. It uses a simple neural network implemented in PyTorch to predict prices based on given features. The training process is documented in `train_model.py`.
---
## 📌 Future Improvements
- 📈 Fine-tuning the model with a larger dataset
- 🛠️ Adding more features like **brand, location, fuel type**
- 📊 Deploying as a web app for user-friendly interaction
---
## 📜 License
This project is **for educational purposes only** and does not guarantee accurate price predictions. Feel free to modify and use it for learning. ✨
---
## 🤝 Contributing
We welcome contributions! Feel free to fork the repository, open issues, or submit pull requests.
---
### 🔗 Connect with Me
🐦 Twitter: [@surale_pritesh](https://x.com/surale_pritesh)
💼 LinkedIn: [Priteshsurale](https://www.linkedin.com/in/pritesh-surale-927820178/)
Happy Coding! 🚀