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08:54 Automated CI/CD for ML
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Classroom Contents
Building Developer-Centric ML Inference Platforms
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- 1 00:00 Introduction to Developer-Centric ML Inference Platforms
- 2 00:10 Challenges in Building ML Inference Platforms
- 3 02:50 Architectural Foundations for ML Platforms
- 4 06:05 Kubernetes and CRDs in ML Workflows
- 5 08:54 Automated CI/CD for ML
- 6 11:19 Feature Store and Data Pipeline Architecture
- 7 12:13 Model Serving Strategies
- 8 15:05 Monitoring and Observability
- 9 16:15 Organizational Excellence and Team Collaboration
- 10 19:49 Scaling Challenges and Optimization Strategies
- 11 22:16 Security, Compliance, and Governance
- 12 24:10 Future Trends in ML Inference Platforms
- 13 26:02 Conclusion and Final Thoughts
