Mogady

Mogady OP t1_isxaoym wrote

Reply to comment by give_me_the_truth in [D] How frustrating are the ML interviews these days!!! TOP 3% interview joke by Mogady

The data itself was linear and the relation was obvious(at least to one of the binary classes either the 0 class or the 1), so I simply kept adding more features to the classifier and it kept getting higher values, of course, this doesn't give any info about the precision and recall for each class (0, 1)

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Mogady OP t1_isvkmba wrote

Reply to comment by Mogady in [D] How frustrating are the ML interviews these days!!! TOP 3% interview joke by Mogady

and I was able to do many things in the interview (dealing with categorical, strings , numerical, organizing the features as array, applying the models, testing it and get a score) I could do more but simply you can't recall everything, I use HuggingFace literally every day and I have hacked it multiple times to suit my needs, but still, I can't remember how to import the LM head without searching or how to access the attention layer.

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Mogady OP t1_isvk1jz wrote

Reply to comment by RockyMcNuts in [D] How frustrating are the ML interviews these days!!! TOP 3% interview joke by Mogady

thanks for the resource, but maybe I didn't show that in the post properly, I can do all of that and I know about it :D it is not that I'm rusty, it is just when I do all of these EDA, plots, and experiments, I don't pay attention to every line I write so that I can recall it without searching again. even If I was working with kind of problems recently I would search how to remove Nan rows from a Numpy array millions of times and copy the same one-line code. This is simply how I work, I understand Numpy and I know which functions I need to use it is just I don't spend time focusing all the details.

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Mogady OP t1_isti0cl wrote

Reply to comment by Azmisov in [D] How frustrating are the ML interviews these days!!! TOP 3% interview joke by Mogady

who said I only specialize in NLP, yes this is mainly my experience, but I didn't fail to show how to apply a classifier on a traditional dataset, there is a difference between failing to show the ability to do something, and failing to do it 100% correctly within the given "time-frame". Also, they could have simply ignored my resume.

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Mogady OP t1_isthauc wrote

Reply to comment by Azmisov in [D] How frustrating are the ML interviews these days!!! TOP 3% interview joke by Mogady

No man it doesn't work like that, yes you might be worried if this is the only thing you asked about, but The Nans part came late when I already used almost all the features but the last two had them and I had 5 min left, I can do that easily with Pandas but NumPy is a little complex a[~np.isnan(a).any(axis=1), :], also when you say 97% like you, what is us? let's say this month you worked with tabular data, and the next month you worked with a CV project, are you expected to remember all the syntax of openCV, Pandas, Numpy,Sklearn at that point?

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