AutoML is a powerful tool. It can greatly reduce the time it takes for data scientists to find an optimal model. But common methods like Random Forest, XGBoost, and other “black-box” techniques can make transparency and avoiding bias a challenge, which are especially critical in regulated industries.
XAI bridges that gap, enabling the use of complex models while ensuring transparency for teams and stakeholders.
Join this webinar, hosted by Keith McCormick (Data Science Principal at Further) and Scott Fincher (Data Science Community Team Lead at KNIME)