Linear Algebra

Purpose of this document

Here you find introductory exercises for a workshop on linear algebra. They were written for people who would like to work with data using methods using linear algebra, e.g. Machine Learning. It gives you an overview of fundamental concepts and some fields of application.

The exercises use the Python programming examples using the Numpy library. To work through them, very little Python experience should be sufficient.

Slides and Exercise Notebooks

You can download the material for a 4-hour workshop and open the exercise notebooks on Google Colab:

Document	Colab	Download
Presentation Slides		Download PDF
Vectors	Open in Colab	Download notebook
Matrices	Open in Colab	Download notebook
Linear Transformations	Open in Colab	Download notebook
Distances and Norms	Open in Colab	Download notebook
Recommender	Open in Colab	Download notebook
Linear Equation Systems	Open in Colab	Download notebook
Graph Analysis	Open in Colab	Download notebook
Vectorization	Open in Colab	Download notebook

Contents

• Preparations
• Vectors
• Matrices
• Linear Transformations
• Distances and Norms
• Recommender
• Linear Equation Systems
• Graph Analysis
• Vectorizing Data
• Links

Source Code

github.com/krother/linear_algebra

License

© 2025 Dr. Kristian Rother

The Python code is distributed under the conditions of the MIT License. See LICENSE.TXT for details

The text, exercises and images can be used and distributed under the conditions of the Creative Commons Attribution Share-alike License 4.0 (CC-BY-SA 4.0). See creativecommons.org for details

Contact

kristian.rother@posteo.de