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infimum
·il y a 10 mois·discuss
This sounds super interesting. Can you elaborate on how you apply ZK to ML? (or can you point me to any resources?)
infimum
·il y a 3 ans·discuss
As far as I know, none of these 3 work specifically in NLP, most of their work is in image processing and to the best of my knowledge none of them have any background in linguistics.
infimum
·il y a 4 ans·discuss
Their pricing page says that it costs them around 1$ to serve 80 searches. I really wonder how they arrive at that number. That seems shockingly expensive somehow.
infimum
·il y a 5 ans·discuss
> This seems like such a distant yet specific relationship type

I don't know much about it (never stepped foot outside EU/NA) but apparently some Asian countries have a pretty intricate system of kinship terms. For example Diagram IV in [1] shows different (Mandarin?) Chinese terms for what we would just call a "cousin" in English. I also found the video by NativLang [2] on the topic pretty interesting.

[1] https://ac-journal.org/journal/vol3/Iss3/spec1/huang_jia.htm... [2] https://youtu.be/YOi2c2d3_Lk
infimum
·il y a 5 ans·discuss
scikit-learn (next to numpy) is the one library I use in every single project at work. Every time I consider switching away from python I am faced with the fact that I'd lose access to this workhorse of a library. Of course it's not all sunshine and rainbows - I had my fair share of rummaging through its internals - but its API design is a de-facto standard for a reason. My only recurring gripe is that the serialization story (basically just pickling everything) is not optimal.
infimum
·il y a 5 ans·discuss
lmgtfy: https://en.wikipedia.org/wiki/Nation_state
infimum
·il y a 5 ans·discuss
> Is a hotdog a sandwich?

Depends on whether the bun is cut in half. If yes it's a sandwich otherwise it's a pizza. /s

Arguments about categorizations can be productive in as far as they allow you a glimpse into the thought-process of other people (=
infimum
·il y a 6 ans·discuss
Currently on course 2/4 in the series and it's great. Every week starts with a reading assignment from the RL book followed by a series of videos (re-)explaining stuff. The videos themselves are very nicely structured, with clear outlook and summary at the start and end of them. Sutton himself appears in a couple of videos and there are other great guest lectures with interesting insights about applications.

Definitely a recommendation!