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Interpretable Machine Learning: Exercise 4

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
  1. Install requirements with pip install -r requirements.txt.
  2. 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.
  3. Test all tasks with pytest or specific files with pytest tests/test_*.py.
  4. 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

Dataset from kaggle.

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