Authors: Prashanta Saha & Matt Wong

The main goal of this project is to predict the flight delays from the first 7 days of 2020

Midterm Project Kickoff

Midterm Project Presentation

Midterm Project Submission File

These files were provided to us at the beginning of the project:

• exploratory_analysis.ipynb: The exploratory data analysis contains 10 questions that we needed to answer during the data exploration phase. It helped us get familiar with the variables and dataset.
• data_description.md: Contains the description of all variables across 4 tables in the dataset.
• modeling.ipynb: Contains the instructions for modeling parts of the project.
• sample_submission.csv: Example of the model that is to be submitted

more_eda.ipynb

These were the files we used to clean and manipulate data, and engineer features:

Data Collection.ipynb

Data Cleaning and Feature Engineering.ipynb

These files contain the various models we used:

Base model with Linear Regression.ipynb

Optimized model with Linear Regression.ipynb

ElasticNet Classifier.ipynb

Naive Bayes.ipynb

Poly Regression

ADA Boost Classifier.ipynb

Random Forests.ipynb

SGDRegressor.ipynb

SVR.ipynb

XGBoost.ipynb

We were provided with 4 tables of data from the air travel industry

1. flights
2. passengers
3. fuel_consumption
4. flights_test