In this project for our Machine Learning course, our class was provided with FlightDelays.csv. This file contained information on commercial flights that departed Washington, DC, and that arrived in New York. The objective of the project had been to train supervised learning models to predict whether a flight will be delayed. For the purpose of this project, a delay was defined as an arrival that is at least 15 minutes later than scheduled.

Activities performed included: data preprocessing, model building, and performance evaluation. Algorithms implemented included: Naive Bayes, Classification and Regression Trees (decision trees), and Logistic Regression.

Files in this project:

1. Comparing flight delay predictions.ipynb - a Jupyter notebook to implement the code.
2. Flight delays.csv - a Comma Separated Values file containing the raw flight data.
3. Flight delay predictions report.pdf - a Portable Document File written in IEEE format.