Federated Reconstruction for Matrix Factorization (Building recommendation systems with TensorFlow)

Looking to train models for on-device inference without gathering any sensitive user data? Developer Advocate Wei Wei talks about Federated Reconstruction for matrix factorization, a novel technique for building recommendation systems using TensorFlow Federated (TFF). Follow along as he takes you through a cross-device federated learning example. Resources: Federated learning video→ https://goo.gle/3qttKIM TensorFlow Federated → https://goo.gle/3twlycG Collaborative learning video → https://goo.gle/37Wd0DB Federated Reconstruction for Matrix Factorization → https://goo.gle/3wwBRYP A Scalable Approach for Partially Local Federated Learning → https://goo.gle/3wukl7o Federated Reconstruction for Matrix Factorization tutorial → https://goo.gle/3wwBRYP Federated Reconstruction: Partially Local Federated Learning paper → https://goo.gle/3isZNnx TFF FedRecon libraries → https://goo.gle/3wwhLxG Federated Learning Workshop - FLA Research Demos & TFF Tutorials → https://goo.gle/3D3i2cZ Chapters: 0:00 - Introduction 0:55 - What is federated learning? 1:40 - Cross-device federated learning example 5:42 - Code walkthrough 7:15 - Wrap up Watch more Building recommendation systems with TensorFlow → https://goo.gle/3Bi8NUS Subscribe to TensorFlow → https://goo.gle/TensorFlow product: TensorFlow - TensorFlow Recommenders; fullname: Wei Wei;