Federated Learning: Machine Learning on Decentralized Data (Google I/O'19)

Meet federated learning: a technology for training and evaluating machine learning models across a fleet of devices (e.g. Android phones), orchestrated by a central server, without sensitive training data leaving any user's device. Learn how this privacy-preserving technology is deployed in production in Google products and how TensorFlow Federated can enable researchers and pioneers to simulate federated learning on their own datasets.

Watch more #io19 here: Machine Learning at Google I/O 2019 Playlist → https://goo.gle/2URpjol
TensorFlow at Google I/O 2019 Playlist → http://bit.ly/2GW7ZJM
Google I/O 2019 All Sessions Playlist → https://goo.gle/io19allsessions
Learn more on the I/O Website → https://google.com/io

Subscribe to the TensorFlow Channel → https://bit.ly/TensorFlow1
Get started at → https://www.tensorflow.org/

Speaker(s): Daniel Ramage and Emily Glanz

TDC839 event: Google I/O 2019; re_ty: Publish; fullname: Daniel Ramage, Emily Glanz;