FedML
federated-xgboost
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FedML | federated-xgboost | |
---|---|---|
6 | 1 | |
4,026 | 64 | |
1.9% | - | |
10.0 | 1.2 | |
1 day ago | 12 months ago | |
Python | C++ | |
Apache License 2.0 | - |
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
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Launch HN: Flower (YC W23) – Train AI models on distributed or sensitive data
This is not new at all. There is a much stronger competitor existing in the market already: FedML (https://fedml.ai). They have a much larger open-source community, and a well-managed and widely-used MLOps (https://open.fedml.ai).
- [Discussion] How feasible is it to partition a DNN model into pieces?
federated-xgboost
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Federated XGBoost
Have you seen this github repo? https://github.com/mc2-project/federated-xgboost
What are some alternatives?
flower - Flower: A Friendly Federated Learning Framework
alpa - Training and serving large-scale neural networks with auto parallelization.
experta - Expert Systems for Python
MetisFL - The first open Federated Learning framework implemented in C++ and Python.
HandyRL - HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.
adaptdl - Resource-adaptive cluster scheduler for deep learning training.
secure-xgboost - Secure collaborative training and inference for XGBoost.
hivemind - Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.
mc2 - A Platform for Secure Analytics and Machine Learning
speech-to-text-benchmark - speech to text benchmark framework
auto-split - Auto-Split: A General Framework of Collaborative Edge-Cloud AI
openfl - An open framework for Federated Learning.