Keynote for: "Deep Credit Risk — Machine Learning in Python" by Daniel Roesch and Harald Scheule

My note and coding along with this book. Follow the below steps after cloning this repository to run codes:

Setup

1 Create and activate environment

# Create virtual environment
python -m venv .venv

# Activate it (Windows) - it depends on your OS
.venv\Scripts\activate

2 Make sure your Jupyter notebook uses this env

# Install ipykernel in your virtual environment
pip install ipykernel

# Create a kernel for your virtual environment
python -m ipykernel install --user --name=dcr_env  --display-name "DCR Environment"

3 Install packages

# install the dcr
pip install -e .

# install other dependencies
pip install -r .\requirements.txt

When running the notebook, remember to choose "DCR Environment" under available kernels.

Note

The dcr.py and dcr.csv all credit to the author of the book, these files can be downloaded from the book's website: https://www.deepcreditrisk.com. I just replaced the data definition in the code with:

import os

# Get the directory where dcr.py is located
module_dir = os.path.dirname(os.path.abspath(__file__))
csv_path = os.path.join(module_dir, 'dcr.csv')
data = pd.read_csv(csv_path)