Introduction to Machine Learning using Python

Materials for the SIS machine learning workshop.

Setup Instructions

The setup is based on the Conda distribution for Python called Anaconda (https://www.anaconda.com/products/individual).

I. Install Anaconda

1. If you don’t have Anaconda yet, download and install Anaconda from https://www.anaconda.com/products/individual, or, in case you work on a ETH-managed computer, install Anaconda via the ETH AppV Software Kiosk.

II. Install Conda environment

on MacOS (Intel, aka "non M1 Mac"):

1. Open Terminal.app, change directory to the directory with workshop materials ($ cd path/to/dir) and run:

   $ conda env create -f environment.yml

2. In case the following line prints OK your setup is fine:

   $ conda run -n machine_learning_workshop_2022 python -c "import tensorflow, matplotlib, numpy, pandas; print('OK')"

3. Start jupyter lab using

   $ conda run -n machine_learning_workshop_2022 jupyter lab

on MacOS (ARM, aka "M1 Mac"):

1. Open Terminal.app, change directory to the directory with workshop materials ($ cd path/to/dir). In case you did not install miniforge before (check if the folder miniformge3 exists in your home directory), run first:

   $ ./install_miniforge.sh

2. Then run

   $ conda env create -f environment_m1.yml

3. In case the following line prints OK your setup is fine:

   $ conda run -n machine_learning_workshop_2022 python -c "import tensorflow, matplotlib, numpy, pandas; print('OK')"

4. Start jupyter lab using

   $ conda run -n machine_learning_workshop_2022 jupyter lab

on Linux

1. Open Terminal, change directory to the directory with workshop materials ($ cd path/to/dir) and run:

   $ run conda env create -f environment_linux.yml

2. In case the following line prints OK your setup is fine:

   $ conda run -n machine_learning_workshop_2021 python -c "import tensorflow, matplotlib, numpy, pandas; print('OK')"

3. Start jupyter lab using

   $ conda run -n machine_learning_workshop_2021 jupyter lab

on Windows

1. Start the Anaconda Navigator and Select "Environments"

2. Press "Import Environment" Button.

3. Click at the folder icon; using the File Selection Dialog navigate to the to the directory with workshop materials and select environment.yml file.

4. Press "Import" Button.

5. Click on the green triangle and from the dropdown list select "Open Terminal".

6. Check your setup by running

   python -c "import tensorflow, matplotlib, numpy, pandas; print('OK')"

   in the terminal. If this line prints OK your setup is fine.

7. Check if you can start JupyterLab by running

   jupyter lab

   from the workshop material directory in the terminal. Note that you may need to install Git and reboot if you have not already done so.

Using JupyterLab

The course content is provided as Jupyter Notebooks. Please make sure to familiarize yourself with JupyterLab Interface.

The Setup Instructions include information on how to start JupyterLab in a Web browser.

Preparation Script

The workshop materials contain a 00_numpy_pandas_matplotlib_intro.ipynb Jupyter Notebook with an introduction to NumPy, pandas and Matplotlib libraries, which we are used without further introduction during the workshop. Please prepare yourself and go through the notebook.