Interpretable Machine Learning: Exercise 8

Instructions

1. Install the open-source-distribution anaconda.
2. Create a new environment with python 3.9 and activate it. If you already created an environment for a previous exercise, feel free to reuse it.

conda create -n iML python=3.9
conda activate iML

3. Install requirements with pip install -r requirements.txt.
4. Add your code in all tasks/*.py files according to the exercise sheet. You can run them with python tasks/*.py. All functions are called automatically.
5. Test all tasks with pytest or specific files with pytest tests/test_*.py.
6. Push your solution to your repository.

Code is tested on Linux and Mac only. Testing is not guaranteed to work on Windows or VMs.

Copyright

Junco-bird image from Wikimedia commons under (CC BY-SA 4.0). Wheat Seeds Dataset from kaggle.