FedML VS federated-xgboost

Compare FedML vs federated-xgboost and see what are their differences.

FedML

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, FEDML Nexus AI (https://fedml.ai) is your generative AI platform at scale. (by FedML-AI)
federated-learning Deep Learning distributed-training Blockchain edge-ai Machine Learning on-device-training inference-engine Marketplace Mlops Privacy Security
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fedml.ai
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federated-xgboost

Federated gradient boosted decision tree learning (by mc2-project)
federated-learning federated-xgboost Machine Learning Security
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FedML federated-xgboost
6 1
4,060 64
1.9% -
9.9 1.2
1 day ago about 1 year ago
Python C++
Apache License 2.0 -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

FedML

Posts with mentions or reviews of FedML. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-03-22.

federated-xgboost

Posts with mentions or reviews of federated-xgboost. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-22.

What are some alternatives?

When comparing FedML and federated-xgboost you can also consider the following projects:

alpa - Training and serving large-scale neural networks with auto parallelization.

flower - Flower: A Friendly Federated Learning Framework

experta - Expert Systems for Python

secure-xgboost - Secure collaborative training and inference for XGBoost.

HandyRL - HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.

mc2 - A Platform for Secure Analytics and Machine Learning

adaptdl - Resource-adaptive cluster scheduler for deep learning training.

breaching - Breaching privacy in federated learning scenarios for vision and text

MetisFL - The first open Federated Learning framework implemented in C++ and Python.

AIJack - Security and Privacy Risk Simulator for Machine Learning (arXiv:2312.17667)

hivemind - Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.

keepassxc - KeePassXC is a cross-platform community-driven port of the Windows application “Keepass Password Safe”.

FedML vs alpa federated-xgboost vs flower FedML vs experta federated-xgboost vs secure-xgboost FedML vs HandyRL federated-xgboost vs mc2 FedML vs adaptdl federated-xgboost vs breaching FedML vs MetisFL federated-xgboost vs AIJack FedML vs hivemind federated-xgboost vs keepassxc