juniorAWS Machine Learning
What is AWS S3 role in ML workflows?
Updated May 5, 2026
Short answer
S3 is used for storing datasets, models, and training artifacts.
Deep explanation
Amazon S3 acts as a scalable storage layer for ML pipelines. Data is stored in buckets and accessed during training and inference.
Real-world example
Used to store terabytes of image datasets.
Common mistakes
- Storing data locally instead of S3.
Follow-up questions
- Is S3 secure?
- Can ML run directly on S3?