Project - Airline Passenger Satisfaction

Table of Contents

• Overview
• Technologies Used
• Results
• Prescription

Overview

The given dataset contains an airline passenger satisfaction survey. Our goal is to find what factors are highly correlated to a satisfied or an unsatisfied passenger? and perform predictions.

This project consists of : -

• Using sklearn Pipeline and ColumnTransformer for data transformation.
• Selecting the best ML algorithm based on size of the data and resources, and
• Hyperparameter tuning.

Technologies Used

Results

1. Business class customers tend to be more satisfied.
2. Business travel customers tend to be more satisfied.
3. Customer satisfaction doesn't depend on Gender.
4. Customers provided with services with 4-5 grade tend to be more satisfied.
5. Cleanliness has high influence on satisfaction.

Prescription

1. All the provided services should be of 4-5 grade.
2. Concentrate on Cleanliness.
3. Concentrate on Eco class and personal travel as they are most unsatisfied customer.