Code - Link
Key Notes
- Automated and Scalable Infra for ML
ML Automation Steps
- Data Pipeline
- ML Team
- Production / Deploy / Feedback Mechanism
Key Challenge is integration of all stages of development
- Reproducibility via docker
- Scaling via Kubernetes
Reproducibility
- Share insights
- Deploy Code
Automation process
- Data pipeline
- Feature generation
Production
- Monitoring
- Logging
- Packaging
End to End workflow of Development to Production
Infra
- Deploy
- Monitor
- Train
- Scale it on cloud
Data Pipeline process
Keep Thinking!!!
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