FedML
MetisFL
Our great sponsors
| FedML | MetisFL | |
|---|---|---|
| 6 | 43 | |
| 4,060 | 530 | |
| 1.9% | 0.0% | |
| 9.9 | 9.3 | |
| 4 days ago | 6 months ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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
-
[Experiment] The future of AI is open-source, and here is the plan
FedML https://github.com/FedML-AI/FedML might already provide a lot of tools to do the job
- Awesome-Federated-Learning: A curated list of federated learning publications, re-organized from Arxiv (mostly).
-
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).
-
FedML has just released its completely revamped and redesigned AI Platform and Website.
Website: https://fedml.ai Platform: https://open.fedml.ai/
- FedML AI platform releases the world’s federated learning open platform on the public cloud with an in-depth introduction of products and technologies!
- [Discussion] How feasible is it to partition a DNN model into pieces?
MetisFL
- [D] Scaling Neuroscience Research Using Federated Learning
-
We created an open source SDK. Any feedback is important for us!
We have created a new project on GitHub called MetisFL, a federated learning framework that allows developers to federate their machine learning workflows and train their models across distributed datasets without having to collect the data in a centralized location.
- Show HN: New GitHub Project Help Needed
- A lighting-fast and developer-friendly Federated Learning SDK
- Looking for open source developers on GitHub
- Enterprise-ready and developer-friendly Federated Learning SDK
What are some alternatives?
federated-xgboost - Federated gradient boosted decision tree learning
webdevamin - My freelance web agency website
alpa - Training and serving large-scale neural networks with auto parallelization.
AIJack - Security and Privacy Risk Simulator for Machine Learning (arXiv:2312.17667)
experta - Expert Systems for Python
upvpn-app - UpVPN is the world's first Serverless VPN. The VPN app is available for macOS, Linux, Windows, and Android. The UpVPN service can also be used with any WireGuard compatible client using the Web Device feature.
HandyRL - HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.
frugally-deep - Header-only library for using Keras (TensorFlow) models in C++.
adaptdl - Resource-adaptive cluster scheduler for deep learning training.
billabear - Subscription Management and Billing System
hivemind - Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform