Maybe useful

A Gentle Introduction to Graph Neural Networks https://distill.pub/2021/gnn-intro/

yeah I hear you ... I've been rejected for stupid shit many times

I applied to a similar platform, maybe same, first question was to do linear regression just with linear algebra, I couldn't remember all the details to save my life, got maybe 20% there. second question was, here's a random data set, do the eda and model, and I crushed it with 10 minutes to spare, they said almost no one finished it. because a bank had asked me similar stuff and it was a little shaky so I practiced every day for a week or two. the bank also asked me some bullshit dynamic programming leetcode stuff that I hand-waved through and that's prob why they rejected me, it was pretty silly.

the tough love: interviewing is ALWAYS a signaling problem that doesn't line up perfectly with the job. the onus is on you to solve for the test. maybe it's an arbitrary test but if you hack it you show you have the desire and focus and ability to get something arbitrary done. the good news is, if the top candidates know dropna() off the top of their head, if you practice for a week, so will you. there's a time to vent a little and then the time to do da 'ting dat de doctor ordered.

don't sweat it too much, rejection happens, I know it doesn't feel good.

for pandas this is pretty good https://www.dunderdata.com/blog/minimally-sufficient-pandas

for the data science interview this is guy is OK - https://www.nicksingh.com

sounds to me like you're just a little rusty on the plain vanilla ML, every day for a week or two grab a free data set from a site and try to model it in 1 hour

https://r-dir.com/reference/datasets.html

use pandas-profiling and seaborn pairplot for EDA , or try the EDA tools out there https://builtin.com/data-science/EDA-python

use an automated hyperparameter optimization routine for e.g. XGBoost with Optuna or Hyperopt

you'll crush it!

it's not a bad skill to have to do quick and dirty EDA and basic ml or automl on a data set for a good baseline. I prefer that sort of interview because it's directly related to the skills you use on the job, it's not a crazy time-consuming take-home, it's not these really open-ended questions like how do you build Google Maps from scratch where they are looking for some very specific concepts and if you miss them you're SOL.