You're building a training data pipeline and need a consistent way to deal with incomplete records before they reach downstream models. Some fields are optional, some are critical, and missing values can come from source gaps, late data, or parsing failures.
How would you handle missing data in a dataset?
You're building a training data pipeline and need a consistent way to deal with incomplete records before they reach downstream models. Some fields are optional, some are critical, and missing values can come from source gaps, late data, or parsing failures.
How would you handle missing data in a dataset?
