FM
kennethleungty/Failed-ML
Compilation of high-profile real-world examples of failed machine learning projects
750 50 +0/wk
GitHub
ai artificial-intelligence classification computer-vision data-engineering data-quality data-science deep-learning failed-data-science failed-machine-learning failed-ml fml
Trend
0
Star & Fork Trend (30 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
kennethleungty/Failed-ML has +0 stars this period . Velocity data will be available after more historical data is collected.
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Signal-backed technical analysis will be available soon.
| Metric | Failed-ML | Deeplearning.ai-Natural-Language-Processing-Specialization | prompt-layer-library | causal-ml |
|---|---|---|---|---|
| Stars | 750 | 750 | 749 | 749 |
| Forks | 50 | 502 | 76 | 134 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | N/A | Jupyter Notebook | Python | N/A |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | GPL-3.0 | Apache-2.0 | N/A |
Capability Radar vs Deeplearning.ai-Natural-Language-Processing-Specialization
Failed-ML
Deeplearning.ai-Natural-Language-Processing-Specialization
Maintenance Activity 0
Last code push 664 days ago.
Community Engagement 33
Fork-to-star ratio: 6.7%. Lower fork ratio may indicate passive usage.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 95
Licensed under MIT. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.