The most "interesting" questions my non-technical co-workers asked to me:
1. "What do you need it for?" -> referring to my second monitor, aehm I don't know, look at stuff on it?
2. "Why the printer isn't working?" -> gosh, I wish I was ever able to make one of those work at all, let alone understand why they don't work
3. "Is it possible?" -> guys, I'm tired, basically everything is possible in this space given enough time and resources, stop asking and then avoid allocating resources to projects
OMFG I'M THE HAPPIEST PERSON ALIVE!
(The Darth Vader mask in the center is the original one used in the force strikes again, the T-Rex is the original one used to model the digital one, and the RoboCop costume is an original as well)
P.S.: I swear the shirt wasn't planned it all happened by accident
Infosec researchers find free access to a huge database of unencrypted passwords AND biometric data
Let me get this straight: we're living in one of the most easy growth ages thanks to technology (look at Google, Facebook, Amazon, etc), but companies are borrowing money to give them back to shareholders instead of investing them, and banks say that if "managers" who are expert in their fields it means that there aren't good investments possibilities on the horizon. I'd say ditch the managers, they were always useless anyway and let workers spur innovation https://www.bloomberg.com/news/articles/2019-08-08/companies-use-borrowed-billions-to-buy-back-stock-not-to-invest
The guys tending the last working Olivetti Mainframe in a Tuscan High School are my new personal heroes
I find weird people boasting facts like "80% of views on Netflix and 60% of clicks on YouTube come from a recsys" as if it was a huge win.
It is surely a win, but not that great. I focus on the 20% of views on Netflix that came from people using one of the worst and most hidden ways to search on an app.
On Netflix the recsys is almost the only way to find content, and so I consider YouTube's as a larger win, though the home page and the recsys behind are becoming more and more "in-your-face" like Netflix's
Today I was reminded once again what is the most difficult thing in data science: politics.
Time to get back to this evergreen https://www.rdisorder.eu/2017/09/13/most-difficult-thing-data-science-politics/
A good advice for any programmer is to better understand why conciseness if used correctly it's way better at conveying meaning than verbosity (Java I'm looking at you).
Because of this reading the works from Italo Calvino and especially https://en.wikipedia.org/wiki/Six_Memos_for_the_Next_Millennium is really helpful.
Hemingway would be good as well, but I find the latter less "in the face" than the former, who's also usually very funny to read! (pick almost any novel and you're sure to get a couple of laughs out of it)
I'm announcing panthera: a #Clojure wrapper around pandas and numpy for all your data sciencey work!
The library is still alpha, but there's already a lot of stuff to have fun with. So give it a run, if you like it star it and any kind of feedback is accepted!!!
Oh jeez, I can't even... Instagrammers are the dumbest ever, luckily it appears many of them will die by poisoning from this lake.
I've been there years ago (for completely different reasons) and "stay away from the lake" was one of the first things they told us
Apparently people are moving from Excel to Jupyter notebooks, and this is so wrong on so many levels! https://towardsdatascience.com/jupyter-is-the-new-excel-but-not-for-your-boss-d24340ebf314
I really like the 80 columns rule, it makes easier to read and understand things (try looking at newspapers and magazines, most of them stick to something close to 80 or even lower) and it is a good rule of thumb to evaluate languages: your language makes it difficult to stick to the 80 columns rule? Change language
Users will be given refunds but the books themselves will no longer be readable. If you made notes on the titles, you'll get $25 credit as a, "we're sorry you'll no longer have access to the notes you took on all those books. Here's $25 and we'll call it even!"
I build data products, some call me data scientist, some data engineer, some software developer.
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