The goal is to predict whether a client will subscribe to a fixed-term deposit (y) based on the Bank Marketing dataset on UCI.

The main notebook for data preprocessing and model training can be found under main.ipynb.

• config contains the path configurations for the loaded data and final models
• notebook contains the main notebook
• utils contains the definitions and groupings of the column names

• Dependencies are managed via pipenv. Before setting up the virtual environment, please install pipenv.
• To set up the virtual environment, run pipenv install -e .
  • if you encounter problems, try deleting the Pipfile.lock
• To enter the virtual environment, run pipenv shell
• Run jupyter notebook and follow the link displayed in your terminal

• The jupyter notebook will automatically download the data from UCI and store it under the path specified in config/paths.py.