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Machine Learning System Design
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Module 2
Data Management and Governance in ML
1
Designing Batch and Streaming Ingestion Pipelines
Design data ingestion pipelines for both batch and streaming sources.
2
Data Architectures for ML: Lake, Warehouse, and Lakehouse
Compare data lake, data warehouse, and lakehouse architectures for ML use cases.
3
ML Data Validation & Quality Monitoring
Design a data validation and quality monitoring strategy for an ML pipeline.
4
Data & Schema Versioning for Reproducibility
Design a strategy for data and schema versioning to ensure reproducibility and track lineage.
5
ML System Monitoring & Debugging: Logging & Event Architecture
Design a logging and event collection architecture for monitoring and debugging ML systems.
Previous module
Foundations of Distributed Systems for ML
Next module
Feature Stores and Engineering at Scale