Customer Purchasing Power of Car

Keywords: Prediction of, customer

Background

Purchasing of cars has been increasing in recent times due to the increase in the purchasing power of the customers. It is very important for the car sellers to estimate the purchasing capacity of the customers to improve the sales of the vehicles. The main challenge in this project is to estimate the overall amount that a person could be able to spend on busing a vehicle. It depends on many factors like personal interest, assets and many others which can’t be predicted. Here, we are using ANN in Deep Learning to predict the purchasing price that a customer can afford. ANN will be trained with customer related information like country, age, salary, credit card debt, and net worth. The main aim is to forecast the net amount that a customer could likely spend. the model provided a 97.2 of r2 score.

Aim & Objectives

Aim
To Predict the Car Power of Customer Purchasing Using DL Methods
Objective
Develop a deep learning model to predict car purchasing power based on customer data.
Train the model with customer profiles for precise power level classification.
Assess the model's accuracy to offer reliable insights into customer car purchasing capacity using DL techniques.

Research Methodology

ANN Technique used

Software & Tools

Jupyter, Google Collab

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