Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (4.6%) to scientific vocabulary
Last synced: 10 months ago
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Repository
Basic Info
- Host: GitHub
- Owner: Aleem2
- License: bsd-2-clause
- Language: Python
- Default Branch: main
- Size: 463 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Created over 2 years ago
· Last pushed over 2 years ago
Metadata Files
Readme
License
Citation
README.md
Federated Learning Implementation using Flower Framework
This repository is created to test out the Flower library and understand how federated learning works.
Implementation details: 1. A container image is created with Flower and Scikit-learn to test out Minist data set. 2. This same container image is used to create three containers working as Server, Client 1 and Client 2. 3. Secure communication is established using gprc protocol and self-signed certificates using Flower's script.
To do - Use this same implementation across different TREs and different clusters to test functionality.
Owner
- Login: Aleem2
- Kind: user
- Repositories: 20
- Profile: https://github.com/Aleem2
Citation (citation.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - family-names: "Uddin" given-names: "Aleem" orcid: "https://orcid.org/0000-0002-8519-5534" title: "flower" version: 1.0.0 doi: 10.5281/zenodo.1234 date-released: 2024-02-28 url: "https://github.com/Aleem2/flower"
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Dependencies
Dockerfile
docker
- python 3.8 build
server-config/pyproject.toml
pypi
- flwr >=1.0,<2.0
- flwr-datasets >=0.0.2,<1.0.0
- python ^3.8
- scikit-learn ^1.1.1
server-config/requirements.txt
pypi
- flwr >=1.0,<2.0
- flwr-datasets >=0.0.2,<1.0.0
- numpy *
- scikit_learn *