Blog

Learn to adapt Flower for your use-case.

Speech models, federated! (SpeechBrain x Flower)

Daniel J. Beutel

Federated Speech Model Training via SpeechBrain and Flower.

Federated Scikit-learn Using Flower

Kaushik Amar Das

Scikit-learn models can now be trained on distributed data with Flower.

What is the Carbon Footprint of Federated Learning?

Xinchi Qiu

Comparing the carbon footprint of centralized and federated machine learning using Flower.

Running MXNet Federated - MXNet meets Flower

Dr. Maria Börner

MXNet is a highly efficient and flexible machine learning framework. With Flower you can now build MXNet federated learning workloads for the very first time.

PyTorch: From Centralized To Federated

Dr. Maria Börner

Federated your existing PyTorch machine learning projects with Flower.

Google Summer of Code: Project Ideas

Dr. Maria Börner

List of Ideas for Google Summer of Code 2021

Single-Machine Simulation of Federated Learning Systems

Taner Topal

How can we simulate a full Federated Learning system on a single machine?

Running Federated Learning applications on Embedded Devices

Javier Fernandez-Marques

Federated Learning is catching traction and it is now being used in several commercial applications and services. Check how you can deploy FL applications on Embedded Devices.

Federated Learning in less than 20 lines of code

Daniel J. Beutel

Can we build a fully-fledged Federated Learning system in less than 20 lines of code? Spoiler alert: yes, we can.

Hello, Flower Blog!

Daniel J. Beutel

Today we are launching the Flower Blog!