fogml 0.0.3

Tiny Federated ML for Fog Computing

FogML

Due to the development of IoT solutions, we can observe the constantly growing number of these devices in almost every aspect of our lives. The machine learning may improve increase their intelligence and smartness. Unfortunately, the highly regarded programming libraries consume to much resources to be ported to the embedded processors.

The structure of the project is as follows:

• the generators folder contains the source code generators for machine learning models i.e.: naive bayes, decision trees and neural nets;
• the demos folder contains the example MNIST digit recognition for Arduino board and the simple TFT touchscreen.

If you think that the project is interesting to you, please cite the paper: Tomasz Szydlo, Joanna Sendorek, Robert Brzoza-Woch, Enabling machine learning on resource constrained devices by source code generation of the learned models, ICCS 2018