Western-OC2-Lab/AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics

Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning

627 110 +0/wk

GitHub

automated-machine-learning automl concept-drift data-preprocessing data-stream-processing data-streams deep-learning feature-engineering hyperparameter-tuning intrusion-detection-system iot iot-data-analytics

Trend 0

Star & Fork Trend (17 data points)

Stars

Forks

Multi-Source Signals

GitHub

stars 627

forks 110

Growth Velocity

Western-OC2-Lab/AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics has +0 stars this period . Velocity data will be available after more historical data is collected.

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Metric	AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics	AI-ML-cheatsheets	kornia-rs	BMSG-GAN
Stars	627	627	627	627
Forks	110	205	186	103
Weekly Growth	+0	+1	-1	+0
Language	Jupyter Notebook	N/A	Rust	Python
Sources	1	1	1	1
License	MIT	N/A	Apache-2.0	MIT

Capability Radar vs AI-ML-cheatsheets

AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics

AI-ML-cheatsheets

Maintenance Activity 0

Last code push 694 days ago.

Community Engagement 88

Fork-to-star ratio: 17.5%. Active community forking and contributing.

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.