Mark_Neznansky
15
1
26
Mark_Neznansky has not written any posts yet.
Mark_Neznansky has not written any posts yet.
It might be astonishing, but this is fundamentally how word embedding works, by modelling the co-distribution of words/ expressions. You know the "nudge, nudge, you know what I mean" Python sketch? Try appending "if you know what I mean" to the end of random sentences.
Funny. I've used triumphant LoTR music once to overcome my terrible fear of heights. I was climbing mount Kathadin with friends (including passing along "Knife Edge "), and the humming/singing out loud this music (+imagining a chopper-camera shooting from above) has completely effaced my fear. Possibly being called "Legolas" during middle-school and high-school helped, too.
It was to be expected-- Someone had already created a "hierarchy Tags" addon: https://ankiweb.net/shared/info/1089921461
I haven't used it myself, but a comment there said "Simple, nice, and easy."
This is an idea I had only toyed with but have yet to try in practice, but one can create meta-cards for non-data learning. Instead of creating cards that demand an answer, create cards that demand a drill, or a drill with a specific success outcome. I find it a bit hard to find "the best example" for this, perhaps because the spectrum of learnable-skills is so broad, but just for the sake of illustration: if you're learning to paint, you can have "draw a still object", "draw a portrait", "practice color", "practice right composition", "practice perspective" &c, cards. After you finish your card-prompted drill, you move to the next card. Or if you're... (read more)
This is not quite a "tech-tree" dependency structure, but you can use tags to stratify your cards and always review them in sequence from basic to dependent (i.e., first clear out the "basic" cards, then "intermediate", then "expert"). Even if the grouping is arbitrary, I think you can go a long way with it. If your data is expected to be very large and/or have a predictable structure, you can always go for a "multiple-pyramid" structure, i.e, have "fruits basic" < "fruits advanced" < "fruits expert", "veggies basics" < "veggies pro" tags &c, and perhaps even have an "edibles advanced" > veggies & fruits tag for very dependent cards.
On the assumption that... (read more)
Just to comment on the last bit: It seems odd to me that you stress the "3 weeks BARE minimum" and the "crossing point at 3 to 6 months" as a con, while you have used SRS for three years. Given that SRS is used for retention, and assuming that 6 months is the "crossing point", one would think that after three years of consistent SRS use you'd reap a very nice yield.
I know it's a metaphoric language, but it seems additionally ironic that the "BARE minimum" you stress equals to your frequency of exams, while you disfavor the cloze deletion's tendency to teach "guessing the teacher's password".
Is the advice perhaps against using SRS to learn/cram complex knowledge under a very limited time?
Being new to this whole area, I can't say I have preference for anything, and I cannot imagine how any programming paradigm is related to its capabilities and potential. Where I stand I rather be given a (paradigmatic, if you will) direction, rather than recommended a specific programming language given a programming paradigm of choice. But as I understand, what you say is that if one opts for going for Haskell, he'd be better off going for F# instead?
I was thinking in a similar direction. From a biological perspective, computation seems to be a costly activity --- if you just think of the metabolic demand the brain puts on the human being. I assumed that it is very different with computer, however. I thought that the main cost of computation for computers, nowadays, is in size, rather than energy. I might be wrong, but I assumed that even with laptops the monitor is a significant battery drainer in comparison to the actual computer. (sorry, mainly thinking out loud. I better read this and related posts more carefully. I'm glad to see the restriction on computations per amount of time, which I thought was unbounded here).
Regarding the bar charts. Understanding that 100 nokens were sampled at each radius and supposing that at least some of the output was mutually exclusive, how come both themes, "group membership" and "group nonmembership" have full bars on the low radii?