This series is designed to help business process owners and privacy program personnel understand basic concepts about differential privacy and applicable use cases and to help privacy engineers and IT professionals implement various tools.
This series focuses on federated learning, an approach that addresses the fundamental privacy challenge of traditional machine learning by avoiding the centralized collection of training data.