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debnsuma/fcc-ai-engineering-aws
A Practical Course on Embeddings, RAG, Multimodal Models, and Agents with Amazon Nova.
197 120 +0/wk
GitHub
amazon-bedrock amazon-nova embeddings multimodal rag
Trend
0
Star & Fork Trend (18 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
debnsuma/fcc-ai-engineering-aws has +0 stars this period . Velocity data will be available after more historical data is collected.
Deep analysis is being generated for this repository.
Signal-backed technical analysis will be available soon.
| Metric | fcc-ai-engineering-aws | diffbot-kg-chatbot | amazon-bedrock-rag | openclaw.net |
|---|---|---|---|---|
| Stars | 197 | 197 | 196 | 196 |
| Forks | 120 | 46 | 54 | 32 |
| Weekly Growth | +0 | +0 | +0 | +1 |
| Language | Jupyter Notebook | Jupyter Notebook | JavaScript | C# |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | Apache-2.0 | MIT-0 | MIT |
Capability Radar vs diffbot-kg-chatbot
fcc-ai-engineering-aws
diffbot-kg-chatbot
Maintenance Activity 0
Last code push 310 days ago.
Community Engagement 20
Fork-to-star ratio: 60.9%. 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.