This repo contains an Assignment for betclick

• clone the repo
• `pip install -r "requirements.txt"``
• cd ./src

Run with docker:

change env variable PASSWORD in docker-compose sudo docker-compose up --build

• fit the model on data using: python main.py

The script will: - download the data, and optionnally ask a password for unzipping - label the data and drop leaky rows - preprocess and write serializables necessary for inference on disk

python main.py --predict

• predict whether each customer in a subsample of the dataset is a potential churner.
• write a file on disk in the preds folder the first column rerpresents customer_key the second column is the target

python main.py --predict --private_file "my_data_file.csv"

The data should have the same format as the original one, it might be necessary to handle mix typed columns.