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jphall663/awesome-machine-learning-interpretability
A curated list of awesome responsible machine learning resources.
4.0k 625 +1/wk
GitHub
ai-safety awesome awesome-list data-science explainable-ml fairness interpretability interpretable-ai interpretable-machine-learning interpretable-ml machine-learning machine-learning-interpretability
Trend
3
Star & Fork Trend (17 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
jphall663/awesome-machine-learning-interpretability has +1 stars this period . 7-day velocity: 0.1%.
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| Metric | awesome-machine-learning-interpretability | deepchecks | Tensor-Puzzles | LLM-RL-Visualized |
|---|---|---|---|---|
| Stars | 4.0k | 4.0k | 4.0k | 4.0k |
| Forks | 625 | 291 | 363 | 379 |
| Weekly Growth | +1 | -1 | +0 | +15 |
| Language | N/A | Python | Jupyter Notebook | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | CC0-1.0 | NOASSERTION | MIT | NOASSERTION |
Capability Radar vs deepchecks
awesome-machine-learning-interpretability
deepchecks
Maintenance Activity 91
Last code push 23 days ago.
Community Engagement 78
Fork-to-star ratio: 15.6%. Active community forking and contributing.
Issue Burden 70
Issue data not yet available.
Growth Momentum 41
+1 stars this period — 0.02% growth rate.
License Clarity 95
Licensed under CC0-1.0. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.