waltherg

Great write-up, thank you. Do you have rough measures for what constitutes high/mid/low- dimensional data? And how do you use XGBoost et al for multi-step forecasting, I.e. in scenarios where you want to predict multiple time steps in the future?

OP pointed out that meetings and projects have happened remotely anyways for a long time - an experience I share. The peers you describe aren’t in the same place as yourself even if you’re both in some office.

Yes, I read this and was thinking therapy from the start. I was never against therapy but finally pulled through and my mood and outlook have improved dramatically over the past six months thanks to my weekly therapy sessions.

OP’s username seems somewhat German so I would cordially invite OP to make use of our pretty decent Krankenkasse system that makes it a relative breeze to get therapy sessions. Shop around if you don’t vibe with your therapist.

Come on mate what's with the pessimism. When did the rich upper class of Italy fail to deliver for the remaining 99% of Italy?

Oh wait ...

Gosh. Did Winterpeg for a year. That was an experience for sure. So long Windypeg.

In the south of Italy where I am right now there appears to be a pattern of pre-lunch and pre-dinner rush hour. You get some pretty decent cycling paths along the sea between 1 pm and 5 pm which turn into what can only be described as death-wish-routes outside that time window.

I thought the point of those ads wasn't that Brave make money but that you accrue those Brave tokens as a representation of your attention and get to send those tokens to publishers of your choice via the browser?

Also, I turned them off as these ads are quite annoying and have a "cheap feel" to them.

The value proof in the backend that convinces advertisers to throw more many at this? Mostly rule of thumb heuristics with a fair amount of overselling. So no, in most cases the telemetry just doesn't prove much.

I've seen the thesis that all this advertising revenue - even if poorly spent - subvents large portions of exciting research in deep learning etc. at the likes of Google and Facebook. So all that talent wouldn't entirely be lost to advertising.

This is a great point and way of looking at it: pandas and SQL live at opposite ends of the maturation level of data wrangling pipelines.

There's usually entire teams involved in preparing these sorts of decks - from content researchers via subject matter experts to designers. So not a single person needs to believe in it all at once.

I think a far better question is: Does whoever is paying for these decks to be prepared believe in them? These decks aren't (always) built for internal use.

So, essentially, you live in Italy where traffic signs and lights are nothing more than street art and some extra frills on the side of the road.

Mice are really into cheese - hence become a mouse to avoid Alzheimer's later in life.

I don't doubt that marketing works but always had a feeling that a lot of it is busy work (e.g. reorganizing AdWords campaign structures every couple of weeks for no apparent reason) and a lot of data-driven success stories probably boil down to right time right place.

Clean randomized experiments naturally provide good answers and are especially feasible in this space but performing those properly, especially with regard to attribution and user identification, presents a whole zoo of issues that are inherently different from what a lot of marketers seem to work on.

I'm intrigued by what you wrote about CNAME records. Could you elaborate on that briefly?

I usually have at least some broad, high level understanding of what tech outside my narrow scope looks like.

Reading the comments here I have zero clue what you're talking about.

Is this what my less technically inclined colleagues feel like when people talk about e.g. machine learning and Python?