Viewing profile — melondonkey

Usually pretty scam savvy but dropped my guard and bought an absolute garbage AI translation of The Little Prince on Amazon. Now I research anything before buying

I think it’s honestly annoying how they feel they have to parenthetically add every time something is a lie or untrue. While their intention is good I think it does a service to no…

Looks like Pokemon Jirachi

The cultural divide between ML engineers and “girls and gays” in data science is very real and in my experience getting worse. Good but rare when the styles can be brought together…

Damn, this is like the fifth time series framework posted this week. This one seems theoretically more interesting than some others but practically less useful. For one, who wants …

Hard to meet everyone where they are and at the same time give them a relevant practical application for their own life. Good learners just soak it up and look for the application …

Data scientist here that’s also tired of the tools. We put so much effort in trying to educate DSes in our company to get away from notebooks and use IDEs like VS or RStudio and da…

One detail I don’t really understand is the low-variance normal component of the target mixture. Would be curious to see from the weights how often that was used

I know. Here I am modeling my data generating process like a chump.

Just needs a less engineering-oriented DS role and will be fine. Consulting is a good way to work in lots of industries and try things on.

I guess I just mean I’m a data scientist—someone who uses models like these in practice as opposed to someone who develops them. I’m not sure what to even make of a term like “foun…

As a practitioner the most impactful library for time series has been brms, which basically gives you syntactic sugar for creating statistical models in Stan. Checks all the boxes …

Weird one minute it feels like the internet is screaming that I’m an out-of-touch dinosaur for using R and the next a simple link to its most popular IDE makes the front of HN.

This is interesting. Are BART models differentiable? I haven’t looked closely at them but I would have thought for posterior sampling they’d have to be. BART has been around for a …

What? Can you explain the mechanism than a NN can “extrapolate” an invoice where a tree model couldn’t? This is all just how the modeler builds the features. Also all models are a …

More dashboards need this I think. I’ve also added relative standard error values on aggregations before to serve as a reliability filter that doesn’t even show users data when the…

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At this point I wish every junior DS could read this paper and not come in to every problem with the new bright idea that they’re going to beat XGBoost with their DL architecture. …

This explanation doesn’t make sense to me. What do you mean by “linearize your data”—tree methods assume no linear form and are not even monotonically constrained. Classification i…

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