This is a binary classification problem, The goal is to predict which of the two levels of satisfaction with the airline the passenger belongs to: Satisfaction, Neutral or dissatisfied
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Updated
May 1, 2024 - Jupyter Notebook
This is a binary classification problem, The goal is to predict which of the two levels of satisfaction with the airline the passenger belongs to: Satisfaction, Neutral or dissatisfied
Apache Hive Hadoop Airline Analysis
Power BI dashboard for analyzing 2015 airline cancellations and flight delays. Includes flight duration, delay and cancellation reasons, date, flight number, airline, airports, and scheduled/actual times. Visualizations show total flights, cancellations, delay reasons, and monthly trends.
Dual-domain AI framework for airline RM and digital analytics validation
Customer Segmentation in Airlines Using Unsupervised K-Means Modeling
AI-powered platform for intelligent operations in healthcare, pharma, and aviation.
A Data Warehouse project analyzing 2022 U.S. domestic departures, delays, cancellations, and weather-related disruption patterns through ETL, dimensional modeling, and Tableau dashboards.
End-to-end EDA on 300,153 Indian airline flight bookings | Analyzing price patterns across airlines, routes, departure times, booking windows & travel classes using Python, Pandas & Seaborn
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