Privacy-Preserving ML Overview

Get a working map of privacy-preserving ML. Learn the families (federated learning, differential privacy, secure multi-party computation, homomorphic encryption, trusted execution environments, synthetic data), their threat models, performance trade-offs, and a practical decision tree for picking the right tool per use case.