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;

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