RCP1932/federated-learning-with-cryptographic-audit
36
🚀 Implement decentralized federated learning with cryptographic audits for secure, privacy-preserving model training across distributed clients.
What's novel
🚀 Implement decentralized federated learning with cryptographic audits for secure, privacy-preserving model training across distributed clients.
Score Breakdown
Innovation
2 (25%)
Craft
34 (35%)
Traction
6 (15%)
Scope
38 (25%)
Signal breakdown
Innovation
Not Fork+1
Code Novelty+0
Unique Niche+1
Concept Novelty+0
Craft
Ci-1
Tests-1
Polish+0
Releases+0
Has License+5
Code Quality+12
Readme Quality+15
Recent Activity+7
Structure Quality+4
Commit Consistency+2
Has Dependency Mgmt+0
Traction
Forks+0
Stars+6
Hn Points+0
Watchers+0
Early Traction+0
Devto Reactions+0
Community Contribs+2
Scope
Commits+5
Languages+3
Subsystems+5
Bloat Penalty+0
Completeness+6
Contributors+6
Authored Files+8
Readme Code Match+3
Architecture Depth+3
Implementation Depth+8
Evidence
Commits
19
Contributors
2
Files
22
Active weeks
4
TestsCI/CDREADMELicenseContributing
Repository
Language
Python
Stars
1
Forks
0
License
MIT