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.