This repository contains a machine learning project focused on predicting car prices using linear regression. The project addresses the business goal of a Chinese automobile company that aims to enter the US market and compete with established US and European counterparts. The company has partnered with an automobile consulting firm to understand the factors influencing car pricing in the American market, which may differ significantly from the Chinese market.
The Chinese automobile company seeks to gain insights into the factors that impact car pricing in the American market. The key objectives are:
- Identify significant variables that play a role in predicting the price of a car.
- Assess the effectiveness of these variables in describing the price of a car.
The ultimate business goal of this project is to build a predictive model that can accurately estimate car prices based on various independent variables. By understanding the relationship between car attributes and pricing, the management can:
Optimize car design and features to align with target price levels. Formulate an effective business strategy tailored to the dynamics of the US market.
Dataset: https://drive.google.com/file/d/1FHmYNLs9v0Enc-UExEMpitOFGsWvB2dP/view The project utilizes a comprehensive dataset consisting of diverse car types from the American market. This dataset has been collected through extensive market surveys and includes relevant features that influence car pricing. The data will be analyzed, preprocessed, and utilized to train a linear regression model.