D3 project for US flight delay visualization

Comparative analysis of flight delay predictions using naïve Bayes, trees, and logistic regression

Visualize departure and arrival delays for the USA by state

ETL Pipeline to analyze Flight Departures (domestic) in the U.S. in 2022. Questions about flight delays, whether influence, airlines reliability.

This is a brief Insights on causes of flight delay based on Viz and implementation of Airline carrier ranking system based on data of flights to and from Texas ( Bureau of Transportation ) during Jan 2017. Using PandaSQL ( SQL+ Python)

“Using historical data, identify which model best predicts future flight delays and in turn identify top indicators of U.S. domestic flight delays.”

This project uses the RITA dataset by the U.S. Bureau of Transportation Statistics to analyse the different causes of airline delays across +1.9M of different flights.

Use Amazon SageMaker to forecast flight delays (regression model)

This is an assignment to work on publicly available dataset called US commercial passenger carrier flights. This assignment is about predicting delays.

This project is a comprehensive Power BI dashboard analyzing airport operations, focusing on flight delays, time analysis, and detailed flight information to improve efficiency and passenger satisfaction.

Pittsburgh International Airport flight delay prediction

This project shows the amount of delays, on time and early flights Skywest airlines had in the year of 2009. Used Pandas, Tableau, SQLalchemy, machine learning model, and Postgres.

A study on the various reasons behind flight delays using data manipulation and visualization techniques.

Flight Delay Predication. Machine Learning Nanodegree Capstone Project

Analyzing United flight data that contains airline, airport, and weather information from 2019 to build a flight delay predictor, using various supervised learning methods.