MC

GokuMohandas/mlops-course

Learn how to design, develop, deploy and iterate on production-grade ML applications.

3.3k 593 +0/wk
GitHub
data-engineering data-quality data-science deep-learning distributed-ml llms machine-learning mlops natural-language-processing python pytorch ray
Trend 0

Star & Fork Trend (24 data points)

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GokuMohandas/mlops-course has +0 stars this period . Velocity data will be available after more historical data is collected.

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Metric mlops-course awesome-quantum-machine-learning MGM Data-Science-Interview-Resources
Stars 3.3k 3.3k3.3k3.3k
Forks 593 768275758
Weekly Growth +0 +0+0+0
Language Jupyter Notebook HTMLPythonN/A
Sources 1 111
License MIT CC0-1.0Apache-2.0MIT

Capability Radar vs awesome-quantum-machine-learning

mlops-course
awesome-quantum-machine-learning
Maintenance Activity 0

Last code push 601 days ago.

Community Engagement 89

Fork-to-star ratio: 17.8%. 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.