Federated Learning - Machine Learning on Decentralized Data

Learn about federated learning, a technology that enables training and evaluating machine learning models across decentralized devices while keeping sensitive data private. Discover how this privacy-preserving technology is used in Google products and how TensorFlow Federated allows researchers to simulate federated learning on their datasets. The course covers federated computation, secure aggregation, federated learning workflow, and the differences between federated learning and traditional distributed learning. The intended audience for this course includes machine learning enthusiasts, researchers, and pioneers interested in privacy-preserving machine learning techniques.