ML Data Engineering and Feature Store

A typical ML process flow is about

• Load the data
• Explore and Clean the data
• Create features
• Create ML model
• Deploy the ML model for inference/prediction

The problem of this flow is that it ignores the fact that the process has to be repeatable and the data need to be reused.