ml-deployment-helper
ML Deployment Helper
Overview
Bridges the gap between trained models and production systems. Generates deployment artifacts, APIs, monitoring, and A/B testing infrastructure following MLOps best practices.
Deployment Checklist
Before deploying any model, this skill ensures:
- ✅ Model versioned and tracked
- ✅ Dependencies documented (requirements.txt/Dockerfile)
- ✅ API endpoint created
- ✅ Input validation implemented
- ✅ Monitoring configured
- ✅ A/B testing ready
- ✅ Rollback plan documented
- ✅ Performance benchmarked
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