Perform data science on data that remains in someone else's server
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Updated
May 16, 2024 - Python
Perform data science on data that remains in someone else's server
An Industrial Grade Federated Learning Framework
Flower: A Friendly Federated Learning Framework
FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.
A unified framework for privacy-preserving data analysis and machine learning
Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)
An easy-to-use federated learning platform
Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data
We expose this user-friendly algorithm library (with an integrated evaluation platform) for beginners who intend to start federated learning (FL) study
A PyTorch Implementation of Federated Learning http://doi.org/10.5281/zenodo.4321561
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
The first open Federated Learning framework implemented in C++ and Python.
Federated Learning Benchmark - Federated Learning on Non-IID Data Silos: An Experimental Study (ICDE 2022)
Benchmark of federated learning. Dedicated to the community. 🤗
FedScale is a scalable and extensible open-source federated learning (FL) platform.
Handy PyTorch implementation of Federated Learning (for your painless research)
Simulate a federated setting and run differentially private federated learning.
Backdoors Framework for Deep Learning and Federated Learning. A light-weight tool to conduct your research on backdoors.
Personalized federated learning codebase for research
An easy-to-use federated learning platform
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