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23:57 Future Trends and Conclusion
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Classroom Contents
Building Apache Spark Clusters on Kubernetes for AI Workloads
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- 1 00:00 Introduction to Cloud Native ML Infrastructure
- 2 00:30 Evolution of ML Infrastructure
- 3 01:16 Challenges in ML Infrastructure
- 4 02:02 Apache Spark and Kubernetes for ML Workloads
- 5 03:25 Components of Cloud Native ML Architecture
- 6 04:14 Spark on Kubernetes: Deployment and Management
- 7 06:59 Dynamic Resource Allocation and Autoscaling
- 8 09:07 Data Management and Persistence
- 9 10:36 Monitoring and Performance Optimization
- 10 13:47 Security in ML Infrastructure
- 11 15:28 Cost Management and High Availability
- 12 18:05 CI/CD and Model Deployment
- 13 22:03 Case Study and Best Practices
- 14 23:57 Future Trends and Conclusion
