Interpretable machine learning (R/Python)


7 hours – 1 day.


  • Basic familiarity with data manipulation (for instance, spreadsheet software).


Random forests, ensemble methods and deep neural networks provide powerful prediction methods. However, they are less transparent as a simpler model, like logistic regression or decision trees. This is a challenge for data scientists, specially with regards to increasing regulation, like GDPR. In this course we cover some of the methods that shed light on the black boxes.

Course Outline

  • Interpreting ensemble models: Random forests, gradient boosting machines.
  • DALEX, LIME and visualization tools (ALE, PDP).
  • Interpreting individual predictions.


  • Marketing specialists, financial analysts, data analysts and data scientists.

Format of the course

  • This is a hands-on course, with live coding and exercises. Participants should bring their own laptops.


150 EUR/person + VAT.

Note:  The course is designed to provide a broad overview. However, we can customize the course to cover your specific needs.

Contact Us