Advancements in Edge and Federated Learning

With increased privacy concerns and the rise of IoT, training models on decentralized data without compromising privacy is becoming more common. Analysts transitioning into ML engineering should study federated learning principles and edge computing frameworks, enabling models to learn from distributed devices while respecting data governance policies.