https://github.com/rohitinu6/indian-used-car-price-prediction
The aim of this project to predict the price of the used cars in indian metro cities by analyzing the car's features such as company, model, variant, fuel type, quality score and many more.
https://github.com/rohitinu6/indian-used-car-price-prediction
algorithms analytics car-price-prediction data-science data-visualization eda machine-learning machine-learning-algorithms python regression used-cars
Last synced: 3 months ago
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The aim of this project to predict the price of the used cars in indian metro cities by analyzing the car's features such as company, model, variant, fuel type, quality score and many more.
- Host: GitHub
- URL: https://github.com/rohitinu6/indian-used-car-price-prediction
- Owner: rohitinu6
- Created: 2025-01-05T02:57:56.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-02-06T03:07:01.000Z (4 months ago)
- Last Synced: 2025-02-06T04:22:07.612Z (4 months ago)
- Topics: algorithms, analytics, car-price-prediction, data-science, data-visualization, eda, machine-learning, machine-learning-algorithms, python, regression, used-cars
- Language: Jupyter Notebook
- Homepage:
- Size: 931 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Indian Used Car Price Prediction
## 📌 Project Overview
This project predicts the price of used cars in India based on various factors such as brand, model, year, fuel type, transmission, mileage, and more. The aim is to help buyers and sellers estimate fair market prices using machine learning techniques.
## 🚀 Features
- Data cleaning and preprocessing
- Exploratory data analysis (EDA) to understand pricing trends
- Feature selection and engineering
- Machine learning model training and evaluation
- Model deployment for real-world predictions
## 🛠 Tech Stack
- Python
- Pandas, NumPy
- Scikit-learn
- Matplotlib, Seaborn
- Jupyter Notebook
## 📂 Dataset
The dataset consists of used car listings with attributes such as:
- **Car Brand & Model**
- **Manufacturing Year**
- **Fuel Type** (Petrol, Diesel, CNG, Electric, etc.)
- **Transmission Type** (Manual, Automatic)
- **Mileage & Engine Capacity**
- **Owner Type** (First, Second, Third Owner)
- **Selling Price** (Target variable)
## 💊 Machine Learning Models Used
- Linear Regression
- Decision Tree Regressor
- Random Forest Regressor
- XGBoost Regressor
## 🔥 Results
The models are evaluated based on RMSE, MAE, and R-squared values. Random Forest and XGBoost provide the best predictions for used car prices.
## 📁 Repository Structure
```
📂 Indian-Used-Car-Price-Prediction
🌍-- 📂 data (Dataset & processed data)
🌍-- 📂 notebooks (Jupyter Notebooks)
🌍-- 📂 models (Trained models)
🌍-- 📂 images (Code and Results Screenshots)
🌍-- 📄 README.md (Project documentation)
```
## 🖼 Code and Results
Include images of code and results in the `images` folder. Example:
## 🐝 How to Run the Project
1. Clone the repository:
```bash
git clone https://github.com/rohitinu6/Indian-Used-Car-Price-Prediction.git
```
2. Navigate to the project folder:
```bash
cd Indian-Used-Car-Price-Prediction
```
3. Install dependencies:
```bash
pip install -r requirements.txt
```
4. Run the Jupyter Notebook or Python scripts to train and test models.
## 🛠 Links
- **GitHub Repository:** [Indian Used Car Price Prediction](https://github.com/rohitinu6/Indian-Used-Car-Price-Prediction.git)
- **Portfolio:** [Rohit Dubey](https://tinyurl.com/dubeyrohit)
- **GitHub Profile:** [rohitinu6](https://github.com/rohitinu6)
- **LinkedIn:** [Rohit Dubey](https://www.linkedin.com/in/rohit-dubey-d/)
- **Twitter/X:** [@rohitdubey003](https://x.com/rohitdubey003)
## 🛣 Tags
`Machine Learning` `Car Price Prediction` `Used Cars` `Regression` `Data Science` `Python` `EDA`
## 📝 License
This project is licensed under the [MIT License](https://opensource.org/licenses/MIT).
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💡 **For any queries or collaboration opportunities, feel free to connect!** 🚀