Interpretable machine learning (R/Python)
Duration7 hours – 1 day.
- Basic familiarity with data manipulation (for instance, spreadsheet software).
OverviewRandom 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.
- 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.
Price150 EUR/person + VAT.
Note: The course is designed to provide a broad overview. However, we can customize the course to cover your specific needs.