It might seem that, we don’t have much choice, because the most popular languages in data science are R and Python or if you prefer Python and R. But today we are not talking about these languages!

During the useR!2022 conference, we can meet with English, Spanish and French. Because of the fact that only English is close to us we created our workshops and papers in this language. But! Is it possible to organize a workshop in another language?

Yes, it can be done and we did it! We submitted workshop in 5 languages in parallel (English, Spanish, Polish, Turkish and Vietnamese)!

Why such an idea?

The idea to conduct a workshop from Introduction to Responsible Machine Learning in several languages was born with the successive language versions of our book.

Our book weaves together theory, examples, and processes relevant to model building under Responsible Machine Learning rules. You will find intuitions and examples for Interpretable Machine Learning and eXplainable Artificial Intelligence. The descriptions are complemented by code snippets with examples in R using the ranger, mlr3 and DALEX packages. Finally, the model development process is shown through a comic strip describing the adventures of two characters, Beta and Bit. The interaction of these two characters shows the decisions that analysts often face, whether to try a different model, a different exploration technique, or to look for different data — questions like how to compare models or verify them.

All the examples are fully reproducible so that you can replicate all these adventures on your local computer. Creating models is a challenging task, but also an exciting adventure. Sometimes manuals focus only on the technical side, losing all the fun. Here we will have both.

You can find our books online for browsing or order a paperback version.

• English. The Hitchhiker’s Guide to Responsible Machine Learning.
• Spanish. La Guía del Viajero al Aprendizaje Automático Responsable.
• Polish. Wprowadzenie do Modelowania Predykcyjnego.
• Vietnamese. 4.0.1 Cùng xây dựng Model Machine Learning với Bêta và Bít.
• Turkish. Sorumlu Makine Öğrenmesi Rehberi.

It was an interesting experience for us, fun that we could do it!

A big thank you to the whole team who prepared the language versions of the book and led the workshop during the conference.

Materials from the conference are available on GitHub.

If you are interested in other posts about explainable, fair, and responsible ML, follow #ResponsibleML on Medium.

In order to see more R related content visit https://www.r-bloggers.com

How many languages do we need to learn about responsible machine learning? useR! 2022 Conference was originally published in ResponsibleML on Medium, where people are continuing the conversation by highlighting and responding to this story.