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

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