Topics / #federated-learning

Federated-learning projects on GitHub

Training ML models across decentralized data without centralizing it.

As of , the most-starred Federated-learning projects on GitHub are awesome-mlops (14.2K stars), PySyft (10K stars) and FractalWorkspace (1.8K stars). GitHub.Locker tracks 5 Federated-learning repositories with 29.7K stars combined. The fastest-growing on October 18 was FractalWorkspace, with +966 stars in a day.

5Projects
29.7KStars in total
+2.9KStars in a day
Browse in the catalog →github.com/topics/federated-learning ↗

Hot right now

Most stars gained in a day · Oct 18

+966

FractalWorkspace

Fractal-Compute-Orchestrations/FractalWorkspace · ★ 1.8K

Fractal is a distributed computing ecosystem that harvests compute from edge devices (like Android phones) to run federated learning and large foundation model inference, while keeping raw user data on-device.

+946

FractalCore

Fractal-Compute-Orchestrations/FractalCore · ★ 1.8K

FractalCore is the central backend orchestrator for the Fractal decentralized compute ecosystem. It coordinates federated learning tasks across Android edge nodes, manages multi-tenant TFLOPs budgets, and runs FedAvg weight aggregation to build a global model.

+944

FractalAndroid

Fractal-Compute-Orchestrations/FractalAndroid · ★ 1.8K

FractalAndroid is an Android client that turns a phone into a privacy-preserving edge compute node for the Fractal distributed intelligence network, running on-device federated learning (TFLite) training in coordination with a central server called FractalCore.

+1

PySyft

OpenMined/PySyft · ★ 10K

PySyft (the 'syft' package) lets you perform data science on data that stays on someone else's server, so researchers can get answers from data without needing a copy or direct access to it.

The all-time top

5 projects · by stars

  1. #1 · visenger/awesome-mlops

    awesome-mlops

    A curated list of references for MLOps (Machine Learning Operations) — links to articles, books, courses, papers, tools and communities about running machine learning systems in production.

    14.2K
  2. #2 · OpenMined/PySyft

    PySyft

    PySyft (the 'syft' package) lets you perform data science on data that stays on someone else's server, so researchers can get answers from data without needing a copy or direct access to it.

    10K
  3. #3 · Fractal-Compute-Orchestrations/FractalWorkspace

    FractalWorkspace

    Fractal is a distributed computing ecosystem that harvests compute from edge devices (like Android phones) to run federated learning and large foundation model inference, while keeping raw user data on-device.

    1.8K
  1. 4

    FractalCore

    1.8KFractal-Compute-Orchestrations/FractalCore · Python

    FractalCore is the central backend orchestrator for the Fractal decentralized compute ecosystem. It coordinates federated learning tasks across Android edge nodes, manages multi-tenant TFLOPs budgets, and runs FedAvg weight aggregation to build a global model.

  2. 5

    FractalAndroid

    1.8KFractal-Compute-Orchestrations/FractalAndroid · Kotlin

    FractalAndroid is an Android client that turns a phone into a privacy-preserving edge compute node for the Fractal distributed intelligence network, running on-device federated learning (TFLite) training in coordination with a central server called FractalCore.

Often tagged together