This book contains the materials for the Statistical Methods seminar of the Data Science and Machine Learning Master’s programme at Carl von Ossietzky Universität Oldenburg. We will explore and discuss the contents of the lecture in a practical way using Python.
How to use this book¶
Every chapter mixes explanation, runnable code and small checkpoints. You get the most out of it by reading with a notebook open next to you and re-running the code with your own changes.
Install Python, Conda and VS Code, or skip straight to Google Colab.
Each teaching block ends with exercises to try yourself.
Many plots in this book can be explored interactively.
A glossary with the recurring symbols, terms, and conventions.
Table of contents¶
Additional resources¶
An Introduction to Statistical Learning: The textbook from the lecture
MLU-Explain: Visual, interactive explanations of core ML ideas
Interactive Machine Learning book: An alternative book with similar content
Machine Learning Demos: Another alternative book with similar content
scikit-learn user guide: References for nearly every model in this book