For efficiency purposes, Betsson is trying to predict which customers are going to call the Customer Service, based on their past behaviour.

For a given day, predict whether a customer will call the Customer Service in the following 14 days.

The main notebooks are numbered in the folder "notebooks":

• 0-eda.ipynb
• 1-feature-selection.ipynb
• 2-predictive-modeling.ipynb
• pycaret.ipynb

The predictions for the test set can be found at predictions/test_predictions.csv.

Additionally, I've created a web app and an API to consume the model. I used Streamlit and FastAPI, respectively.

Links:

• Webapp
• REST API

GitHub Repositories:

• Webapp
• REST API

Docker images:

• Webapp
• Rest API

Note: I'm using the free resources from Render. Downtime might occur (there's limited memory usage as well).