This is a quick introductory course to machine learning, focussing on Jupyter notebooks. It is supposed to be given in one day, to allow people to get first insights in machine learning. Prerequisite is some level of comfort with Python.
This course is not intended to be stand-alone, but to be enjoyed with an instructor. A good part of the material is written by Patrick van der Smagt, with a lot of input from Justin Bayer -- indeed some of the chapters and notebooks -- as well as others. It also borrows heavily from the introduction to ML lecture that Patrick's team gave between 2011 and 2016 at TUM. Some public material from the internet is used, with credits.