This project is a car price prediction model that uses a dataset of car features to predict the price of a car. The dataset used in this project is the Quikr Car Dataset. The dataset contains features of cars such as make, model, year, engine fuel type, etc. The dataset is used to train a machine learning model that can predict the price of a car based on its features.
The Quikr Car Dataset is used in this project. The dataset contains features of cars such as make, model, year, engine fuel type, etc. The dataset is used to train a machine learning model that can predict the price of a car based on its features.
The model used in this project is a Linear Regression model. The model is trained on the Quikr Car Dataset to predict the price of a car based on its features.
To use the car price prediction model, follow these steps:
- Clone the repository:
git clone
- Install the required libraries:
pip install -r requirements.txt
- Run the Jupyter notebook:
jupyter notebook
- Open the
quikr_predictor.ipynbnotebook and run the cells to train the model and make predictions.
The car price prediction model is trained on the Quikr Car Dataset and can predict the price of a car based on its features. The model can be used to predict the price of a car given its make, model, year, engine fuel type, etc.