Welcome to the GitHub repository for the Car Price Prediction Streamlit App! This project aims to provide a user-friendly web application that predicts the price of a car based on various features. The app is built using Streamlit, a popular Python library for creating interactive web applications.
- Predict the price of a car based on its features.
- Explore the dataset and visualize the data.
- Input various car features, such as mileage, brand, year, and more, to get an estimated price.
- The app uses a trained machine learning model to make predictions.
We are pleased to announce that the project has been successfully deployed using Streamlit. You can access the live deployment of the Car Price Prediction model by following this link: Car Price Prediction Deployment
Once you access the Streamlit app, you will be able to interact with the model's user-friendly interface. Simply input the relevant features of the car you want to predict the price for, and the model will provide you with an estimated price based on the trained data. Feel free to experiment with different combinations of features and explore the model's performance.
Your feedback and contributions are highly appreciated. If you encounter any issues, have suggestions for improvement, or would like to contribute to the project, please don't hesitate to create an issue or submit a pull request in this repository.
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Let's start predicting car prices! Enjoy using the Car Price Prediction model deployed on Streamlit.
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Note : This project is for educational purposes only, and the predicted prices should not be considered as definitive values for real-world transactions.
To run the Car Price Prediction Streamlit App on your local machine, follow these steps:
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Clone this repository to your local machine using the following command:
git clone https://github.com/06Neel/Data-Science-Capstone-Project.git -
Navigate to the project directory:
cd car-price-prediction-streamlit -
Create a virtual environment (optional but recommended) and activate it:
python -m venv venv- For Windows:
venv\Scripts\activate - For Unix or Linux:
source venv/bin/activate
- For Windows:
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Install the required dependencies:
pip install -r requirements.txt -
Run the Streamlit app:
streamlit run app.py -
Open your web browser and go to
http://localhost:8501to access the Car Price Prediction app.
The dataset used for this project is included in this repository.
Please download the dataset and place it in the data directory of this repository before running the app.
The repository has the following structure:
car-price-prediction-streamlit/ ├── app.py ├── data/ │ └── comapany.csv ├── models/ │ └── Model.pkl ├── README.md └── requirements.txt
app.py: The main Python script that contains the Streamlit app code.data/: Directory to store the dataset file (comapany.csv).models/: Directory to store the trained machine learning model file (Model.pkl).README.md: This readme file.requirements.txt: List of Python packages required to run the app.
The machine learning model used in the app is trained separately and saved as a serialized file (Model.pkl) in the models directory. If you wish to train your own model, you can refer to the Jupyter Notebook provided in the repository.
Contributions to this project are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request. Let's make this project even better together.
This project is licensed under the MIT License.
We would like to express our gratitude to the following resources for their valuable contributions:
Thank you for visiting this repository. We hope you find the Car Price Prediction Streamlit App useful and enjoy using it!
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