Welcome to FedArtML’s documentation!

Federated Learning for Artificial Intelligence and Machine Learning (FedArtML) is a Python-based software library publicly available on Pypi. The library aims to facilitate Federated Learning (FL) research and simplify the comparison between centralized Machine Learning and FL research results since it allows centralized datasets’ partition in a systematic and controlled way regarding label, feature and quantity skewness. In addition, the library includes existing techniques for generating federated datasets in the relevant state-of-the-art and some other proposed by the authors. Moreover, it contains various metrics for quantifying the degree of non-IID (non-IID-ness) data residing across entities participating in decentralized data.

Access to the official GitHub repo where you can find the library’s source code, the installation command, some getting-started examples (including Jupyter Notebooks), and documentation regarding its use.

Interactive plots:

• InteractivePlots
  • InteractivePlots

Create Federated Data:

• SplitAsFederatedData
  • SplitAsFederatedData