This is a Data Science project aim to enhance the customer experience and streamline the pricing process by leveraging machine learning. You need to create an accurate and user-friendly streamlit tool that predicts the prices of used cars based on various features. This tool should be deployed as an interactive web application for both customers and sales representatives to use seamlessly.
We have historical data on used car prices from CarDekho, including various features such as make, model, year, fuel type, transmission type, and other relevant attributes from different cities. Your task as a data scientist is to develop a machine learning model that can accurately predict the prices of used cars based on these features. The model should be integrated into a Streamlit-based web application to allow users to input car details and receive an estimated price instantly.
This is a step-by-step approach to understand the project :
Install this Necessary Libraries By Using this code:
pip install pandas numpy streamlit scikit-learn scipy matplotlib seaborn