This repository contains a machine learning project that predicts car prices based on various features. The project utilizes a dataset of car listings and employs a regression model to estimate the price of a car given its attributes.

The repository is structured as follows:

• car_price_app/carmodel.pickle: This file is a serialized version of the trained machine learning model for car price prediction.
• car_price_app/encoder.pkl: This file contains the serialized version of an encoder or preprocessing object used to transform categorical variables into a numerical format suitable for the machine learning model.
• car_price_app/app.py: This directory contains a web application for car price prediction. Users can input car details, and the application will return an estimated price based on the trained model.
• data/sampled.csv: This directory contains the dataset used for training and evaluation. It includes car listings with relevant features such as make, model, year, mileage, and more.
• requirements.txt: This file lists all the required Python libraries and dependencies to run the project.

To use this project, follow these steps:

1. Install the necessary dependencies by running the following command:

    pip install -r requirements.txt 

2. Launching the Web Application from Terminal:

   Run gradio car_price_app/app.py script from your command line to start the car price prediction web application.

   NOTE: Make sure you are in the project directory.

3. Convenient URL Access:

   As the application starts, a URL will be displayed in the command line interface. Copy the URL and paste it directly into your browser to access the application.

To enhance the user experience, several engineering techniques were implemented:

1. When you choose a car brand, the available models for that brand will be updated automatically in the model dropdown menu.

2. Similarly, when you choose a car model, the available body types and fuel types will be updated in the body types and fuel types dropdown menus, respectively.

NOTE: The visibility of the car details section is updated when a brand is selected. This means that when you choose a brand, the additional car details section will become visible, including the year, mileage, and other relevant fields.

WEBAPP