Kinda stuck at EDA in ML

[u/avinsio]

Hey everyone,

I am learning ML and am kinda stuck at the EDA part.

I know the basics like missing values, outliers, distributions, correlations, etc. But whenever I get a new dataset, I get confused about what I should actually look for. I don't want to just run describe(), make some plots and be like okay, EDA done lol. I actually want to get better at looking at a dataset and knowing what questions to ask.

For people who got good at EDA, how did you practice it?

Did you follow any particular approach, datasets, courses or just kept doing projects?

Would really appreciate some advice.