*Flow Pipelines

Needs ? Airflow MLFlow
Features Robust scalable scheduler ML artifacts / models / runs tracking 
Easy Infrastructure Fully managed on Astronomer Stateless Standalone Service (Plugs in RDS / S3)
Easy Contributions Describing Pipelines as python actions Writing experiments as python functions / Web UI
Easy Usage Web UI showing logs / failed tasks / click and run Simple but powerful API allowing better collaborations


[1] Data preparation

[2] Data annotation

[3] Run jobs

[4] Record runs & store models / artifacts

[5] Notification

[*]Flow Pipelines

By Florian Dambrine

[*]Flow Pipelines

Design session around Airflow and MLFlow

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