These supplementary notes are roughly connected to the lecture ”Introduction to Machine Learning”. The aim of these notes is to help students getting a deep understanding of the topics discussed in the lecture and exercises. However, we do not claim or guarantee that all topics (from the lecture/exercises) are covered in these notes (since there are minor changes each year). Therefore, the existence of these notes is no excuse for not visiting & attending the lecture and exercises. Furthermore, many topics are covered in far more details than (for just passing the exam) necessary. However, we think that these - more in depth - explanations might be interesting & useful to curious students who want to ”dive deeper” into the material.
