More talks in the program:
A machine learning solution is only as good as it is deemed by the end user. More often than not, we do not think through how results are communicated or measured. If we want users to trust and correctly interpret AI models, we need to make our models transparent and understandable.
In this session, you will learn how to create explainable machine learning models using well-considered interactions and visualizations. We will look at some example cases in the health care sector and marketing sector, which illustrate how UX affects end users perception of AI.