We split up our project into multiple sections, each with their corresponding notebook. Here is some more information:
process_dataset.ipynb- Run this notebook FIRST
- Data cleaning, feature engineering, handling missing values
numerical_analysis.ipynb- Conducts numerical analysis on the data's features and distribution
visualizations.ipynb- Visualizes the data with graphs
machine_learning2.ipynb- Trains several supervised learning classifiers
- Compares results and reports accuracy, precision, recall, and F1
- Warning: running can take a couple hours
All libraries we use are in our requirements.txt file.