Federated Learning 📱

Federated learning is increasingly practical for machine learning developers because of the challenges we face with model and data privacy. In this fully connected episode, Chris and Daniel dive into the topic and dissect the ideas behind federated learning, practicalities of implementing decentralized training, and current uses of the technique.

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Featuring:

• Chris Benson – Website • , GitHub • , LinkedIn • , X • Daniel Whitenack – Website • , GitHub • , X Show Notes:

Learning:

Google Federated Learning comicFederated Learning: A Step by Step Implementation in Tensorflow Frameworks/ open source projects:

TensorFlow FederatedIntel Open Federated LearningPyGridFlower Example uses of Federated Learning:

Federated Learning for Mobile Keyboard PredictionYour voice & audio data stays private while Google Assistant improvesFacebook is rebuilding its ads to know a lot less about youFederated learning for predicting clinical outcomes in patients with COVID-19 Something missing or broken? PRs welcome!

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