About this document

Federated Learning: Challenges and Solutions by azimsohel267452 is a document available to read on EtoBox.

Federated learning involves training machine learning models across multiple decentralized edge devices or organizations while keeping the training data localized. It addresses challenges of privacy and scale in distributed machine learning by allowing local models to be trained on private device data and then aggregated to build a global model without exposing private training examples. Potential applications include predictive features on smartphones without privacy risks, and private predictive healthcar

Author

azimsohel267452

Language

EN