Daily observations on Model building and Feature engineering

 Reality is far from the well-structured features listed. Some things that we discuss on the daily basis

1. Feature not available in the transaction table, asking business users to provide data
2. Currently, it's in excel need to have a process to streamline
3. Feature Data is currently not captured but will be done in future
4. The model overfits because this feature data is currently not captured, Can we leverage/infer through any existing features?
5. The reason for the spike in sales is due to a certain reason which is not captured currently

The question of #Why? #Find? #Add feature data and iterate it is the real crux of learning. Before we talk about feature stores we need to know/collect/understand get all features under one roof.

#datascience #features #perspectives #learning

Domain + Data + Algo,  Connecting, Collecting all of them in a consistent repeatable way with the right data every month only can get consistent results :)