VehiclePricePro is a machine learning-based car price prediction tool that utilizes various data points and algorithms to estimate the value of a car. By analyzing factors such as the car's make and model, year, mileage, condition, and other relevant data, AutoValuate provides users with an accurate estimate of the car's market value. This project is an implementation of the Random Forest Algorithm to predict car prices based on various features.
Dataset The dataset used in this project is sourced from Kaggle. It consists of car specifications such as make, model, year, engine type, fuel type, etc. and the corresponding prices.
Requirements The following libraries are required to run the code:
Pandas NumPy datatime seaborn Scikit-learn Installation
To install the required libraries, run the following command:
Algorithm I'll use various machine learning algorithms to predict the price of used cars.