Setting up the Python environment for exercise 1
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We use conda to manage the Python environment. If you do not have conda yet,
install Miniforge, a minimal conda that uses the community conda-forge channel:

    https://conda-forge.org/download/

(An existing Anaconda or Miniconda installation works as well.)

Open a terminal in this directory (the one that contains environment.yml) and run

    conda env create -f environment.yml

This creates an environment named deep_learning_ex_1 with Python, numpy,
matplotlib, scikit-image and JupyterLab. Activate it with

    conda activate deep_learning_ex_1

and start JupyterLab from this directory:

    jupyter lab

Your browser opens JupyterLab; open the notebooks (*.ipynb) from its file browser.

Alternative without conda: if you have Python 3.10 or newer, you can use a
virtual environment and pip instead:

    python -m venv .venv
    source .venv/bin/activate        (Windows: .venv\Scripts\activate)
    pip install -r requirements.txt
    jupyter lab

Note: the MNIST dataset (about 11 MB) is downloaded automatically the first time
you run logistic_regression.ipynb. It is stored in the MNIST/ subdirectory.
