Welcome to the Data Mining and Machine Learning Book#

This book is a work in progress, that has been initiated as an accompanying source of material for a Bachelor course about data mining and machine learning at TU Eindhoven. The goal of this book is to provide comprehensive and interactive material, delving into the theoretical foundations and practical implementations that underpin the field. We will explore topics such as regression, classification, neural networks, clustering and more. Each concept will be introduced from a theoretical perspective, allowing you to follow the thoughts and considerations that go into designing a method for a given task. Further, we designed practical exercises and examples that hopefully encourage you to experiment with the algorithms discussed and foster a deeper understanding of their functioning.

Transparency is a central theme of this book. By providing rudimentary implementations and step-by-step explanations, we aim to ensure that you have a clear view of the entire process, from theory to practical implementation. We believe that transparency not only facilitates learning but also cultivates the essential skills of critical thinking, problem-solving, and creativity in the realm of machine learning. Even the famous researchers of the field are only cooking with water, and we hope that this book will facilitate you recognizing the cooking mechanisms that are often used and to assess critically the choices made in this cooking process.

Whether you are a novice in the field or possess some prior knowledge of machine learning, this book caters to learners at all levels. We provided the necessary mathematical background in the first chapters and we try to introduce all needed concepts in this book. We only require some basic background in calculus and statistics. The exercises at the end of each chapter offer an opportunity to apply what you have learned and reinforce your understanding.