/car-price-prediction

Prediction of car prices using multiple linear regression.

Primary LanguageJupyter Notebook

car-price-prediction

A toy project with real-world data for prediction of car prices using multiple linear regression.

Business Objective:

GeelyAuto is a privately held global automotive group headquartered in Hangzhou, Chinda. It sold over 1.5 million cars in 2018. Geely Auto aspires to enter the US market by setting up their manufacturing unit there and producing cars locally to give competition to their US and European counterparts.

They have contracted an automobile consulting company to understand the factors on which the pricing of cars depends. Specifically, they want to understand the factors affecting the pricing of cars in the American market, since those may be very different from the Chinese market. The company wants to know:

Which variables are significant in predicting the price of a car How well those variables describe the price of a car

Business Goal:

The goal is to model the price of cars with the available independent variables. It will be used by the management to understand how exactly the prices vary with the independent variables. They can accordingly manipulate the design of the cars, the business strategy etc. to meet certain price levels. Further, the model will be a good way for management to understand the pricing dynamics of a new market.