#38 Explainable Machine Learning with R

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Boyan Angelov | Explainable Machine Learning with R

Modern machine learning algorithms tend to behave as black boxes. We have traded understanding of the inner workings of a model for increases in accuracy and performance. In the era of GDPR and global concerns about data privacy and algorithm bias, understanding how a machine learning model makes a decision has increased importance. Historically there have been numerous efforts in the field, and it is still rapidly developing. This talk is a tour of what recent xAI (explainable AI) methods and associated R tools are available, how they work and some practical stack integration advice. We will cover the packages mlr, lime, iml, dalex, shap, and the sdmexplain (one of his packages).

As usual, short contributions and announcements from the audience are always welcome. We want to be a diverse and inclusive group, please come, bring your friends. We're hoping for a nice crowd enjoying interesting talks and chats.

Our generous host Europace AG will prepare drinks and snacks for us!
See you there

Boyan Angelov

Senior Data Scientist and startup advisor, currently working in management consulting (DAIN Studios). Academic background in bioinformatics. Experience in different fields such as e-commerce, clinical trials, HRTech and open source. Favourite topics in machine learning: natural language processing and spatial models.