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This app is a web-based tool for predicting the price of used cars. It uses a machine learning model trained on a dataset of used car listings to make predictions. Users can input information about a used car (e.g., make, model, year, mileage, etc.) and the app will display the predicted price of the car. The app is built using Flask and incorpor

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Ag994/used-car-Price-prediction-App-using-ML

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Used Car Prediction App

This app is a web-based tool for predicting the price of used cars. It uses a machine learning model trained on a dataset of used car listings to make predictions.

How to use the app

Go to the app's URL in your web browser. Fill in the form with the relevant information about the used car that you want to predict the price for (e.g., make, model, year, mileage, etc.). Click the "Predict" button. The app will display the predicted price of the used car.

Technologies used

Flask: a microweb framework for Python Bootstrap: a front-end framework for styling and layout Pandas: a library for data manipulation and analysis scikit-learn: a library for machine learning

How to run the app locally

Clone the repository to your local machine. Install the required libraries by running pip install -r requirements.txt. Set the Flask environment variables by running export FLASK_APP=app.py and export FLASK_ENV=development. Run the app by running flask run. Go to http://localhost:5000 in your web browser to access the app.

About

This app is a web-based tool for predicting the price of used cars. It uses a machine learning model trained on a dataset of used car listings to make predictions. Users can input information about a used car (e.g., make, model, year, mileage, etc.) and the app will display the predicted price of the car. The app is built using Flask and incorpor

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