aws/amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
11.0k
Stars
6.9k
Forks
71.0
Radar Score
Momentum
Scoring Breakdown
Impact94.8
Velocity59.7
Health49.0
Growth Metrics
7-Day Stars
+6
30-Day Stars
+16
Acceleration
1.88x
Language
Jupyter Notebook
Why it ranks
Strong momentum — adoption is accelerating week over week.
Top 73% globallyLast push 28d ago+6 stars / 7d+16 stars / 30d
🛡️ Enterprise Readiness & Commercial Safety
Organic Growth
83%
High Confidence
License
Permissive (Commercial Friendly)
Safe for commercial use, modification, and distribution.
Health Grade
B
Based on maintenance, issue response, and release cadence.
Radar Score
71.0
Composite of Impact, Velocity, and Health.
Disclaimer: This is an automated heuristic assessment based on public GitHub signals. Always perform your own security audit, dependency review, and legal compliance check before production deployment.
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