Done as Part of Intro to AI Mini Project for coursework at Virginia Tech.
This project aims to analyze the Airline Passenger Satisfaction dataset to gain insights into
factors affecting passenger satisfaction in the airline industry. We will explore the dataset to
identify trends, patterns, and key features of passenger satisfaction. The ultimate goal is to help
airlines enhance their services, improve customer experience, and increase passenger loyalty.
https://www.kaggle.com/datasets/teejmahal20/airline-passenger-satisfaction
Data Collection: Gather and preprocess the Airline Passenger Satisfaction dataset, ensuring
data quality and integrity.
Exploratory Data Analysis (EDA): Perform EDA to gain a deeper understanding of the dataset,
including descriptive statistics and data visualization.
Feature Selection: Identify relevant features that have a significant impact on passenger
satisfaction.
Predictive Modeling: Build predictive models to understand the relationship between key
features and passenger satisfaction.
Recommendations: Provide actionable recommendations to airlines to improve passenger
satisfaction based on the analysis results.
Documentation and Reporting: Document the project process, findings, and recommendations
in a comprehensive report.
● A comprehensive analysis of the Airline Passenger Satisfaction dataset, highlighting key
factors influencing passenger satisfaction.
● Predictive models can be used to forecast passenger satisfaction levels based on
various service aspects and actionable recommendations for airlines to enhance their
services and increase passenger satisfaction.
● A project report summarizing the findings, methodologies, and recommendations.