/data-driven-learning

Fundamentals of Machine Learning (University of Applied Sciences Utrecht)

Primary LanguageJupyter Notebook

Fundamentals of Machine Learning (University of Applied Sciences Utrecht)

ATTENTION: starting from the academic year 2021, this page is no longer maintained. For the current slides and code, please see the Microsoft Teams channel.

What is on Canvas and what is on GitHub?

  • On GitHub: example Notebooks, slides, extra material, exercises (in slides), data sets
  • On Canvas: student manual, assignments, link to webinar recordings, overview of content per week

Examples and exercises

Example code can be found in the Examples folder. During class, exercises will be shown on the slides. The data sets for these exercises can be found in the corresponding example folder. These are exercises you can make during the lesson to test your knowledge. You don't need to submit these.

Resources and tips

Python

Mathematics

Using tools from data science and machine learning would not make a lot of sense without some understanding of mathematics and statistics. However, the focus of the course is on the application of data science, rather than the mathematical foundation. If I use formulas, I will not focus on the technical aspects, but explain what they do conceptually. If you need to catch up on math, you can use these links to the Khan Academy:

Supplemental material by week