Car Price Prediction Model
Overview
This repository contains a machine learning model designed to predict car prices based on various features. Leveraging historical data on car attributes such as make, model, year, mileage, and other relevant factors, the model aims to provide accurate and reliable price estimates for used cars.
Features
Predictive Modeling: Provides price estimates for used cars based on historical data. Data-Driven Insights: Utilizes various car attributes to improve prediction accuracy. Customizable: Easily adaptable to include additional features or data sources.
Installation
Clone the Repository:
Copy code git clone https://github.com/azaz9026/Car_Price_Prediction-_Model/ cd car-price-prediction Set Up the Environment: Create a virtual environment and install the necessary dependencies.
Copy code
python -m venv venv
source venv/bin/activate # On Windows use venv\Scripts\activate
pip install -r requirements.txt
Usage
Prepare Data:
Ensure your dataset is in the correct format. Refer to data/README.md for detailed instructions on data preparation.
Train the Model:
Run the following script to train the model with your dataset:
Copy code python train_model.py Make Predictions: Use the trained model to make predictions:
Fork the repository.
Create a new branch for your feature or fix. Make your changes and test thoroughly. Submit a pull request describing your changes.
License This project is licensed under the MIT License.