Batch Processing Systems for ML Workloads
Batch Processing in ML
Batch systems process large volumes of data at scheduled intervals. They are commonly used for periodic model training and data aggregation.
Advantages
- Cost efficient
- Handles large datasets
- Predictable execution
Batch processing remains essential for offline model training workflows.
