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Clarity comments on Open thread, Nov. 02 - Nov. 08, 2015 - Less Wrong Discussion
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I want to learn to play the Dataridoo. Is Swirl the right choice if I want to graduate into a career in machine learning, but failed at learning Python, and managed to learn Stata? Also I'm shit at concentrating, and it's the only learning platform that doesn't confuse me with all the features. I kid you not I took months to figure out how to use LessWrong. I may be stupid, but I am dedicated. Once I find the best platform for me, I'll stick to it. But good recommendations now may save me months later.
Pardon my candour, but if you are "shit at concentrating", are readily confused by things, and found Python too difficult to learn, then you might want to consider whether machine learning is a good choice of career.
(I gravely doubt that you are in fact stupid, and given sufficient dedication I expect you could do it, but it seems like a lot of pain. Are you sure it's worth it?)
I am fairly confident it will be worth it. I'm not good at a whole lot of other things too. But, big data is said to be a profitable career trajectory in the long term. Most if not everything I do for my career is fairly painful, but I try to enjoy it as I do it and I'm grateful for the experience. The question I ask myself is: what could I be doing instead? And I honestly don't have a lot of better things to be doing anyway, haha.
How strong are your math skills? Did you have IQ testing done?
Mathematicians don't give a shit about IQ. When was the last time you heard Terry Tao talk about IQ?
Writing papers >>>>> psychometrics.
That's because they are an exclusive high-IQ club to start with.
Take someone who scored in 300s on his SAT -- would you recommend him to try to become a mathematician?
What do you suppose Ramanujan's IQ was? Do you think Hardy cared?
No one has any idea since he lived before IQ tests.
That's like saying a basketball coach doesn't care about the player's height, he only cares how high can he jump.
IQ is not like height. Height is a fairly objective physical measurement that is directly relevant for basketball because of the game setup. IQ is the result of a projection of an extremely high dimensional space into a single number that is not directly relevant for mathematics (people do mathematics in an extremely heterogeneous way). Erdos, Ramanujan, and Groethendieck were all top notch and were all very very different from each other. Erdos I think couldn't tie his shoes. Ramanujan was an Indian peasant. Groethendieck wasn't exactly a high functioning individual.
A better analogy would be if a basketball coach cared about "hit points" (determined by whatever methods doctors use, slatestar would know more).
Ramanujan was a Brahmin. "Peasant' isn't quite appropriate.
How is it not "directly relevant"? What do you think the average IQ of mathematicians is, do you imagine it's anywhere close to the population average?
Being able (or not) to tie one's shoes or being an Indian peasant are NOT indicators of IQ. Not being socially successful is not an indicator of low IQ either.
I understand your point that genius mathematicians are really, really weird people. But I see no contradiction there, it's perfectly possible to have high IQ and be really weird.
In NFL they do care about intelligence tests.
I don't claim that they do.
Clarity speaks of himself as stupid and the fact that he failed to learn python is indication of that. If his IQ is <100, I think that would be a valid ground on which to advice him against seeking a career in machine learning.
That's exactly the purpose for which IQ test were designed.
This is only a weak evidence for non-high IQ.
I know a few people who had bad opinion about their IQ, and when I convinced them to take the test, they scored above 130. It's because they believed the stereotype of "high IQ = math prodigy", and they happened to be average at math simply because they focused their lives on something else.
I haven't implied that it's strong evidence, for me the available evidence was enough to raise the question. The answer to that question matters for whether or not to tell him not to seek a career in machine learning.
I do think that for this purpose the testing that tells him that he's above average in math might be enough.
I think it would be useful to taboo "stupid." It is not a useful word.
Tabooing "stupid" is what asking for IQ is about and why I asked about IQ in this context.
Except you are not tabooing anything then, you are just substituing "low IQ" for "stupid." The point of tabooing stupid is to get binary classification out of an inherently complicated multidimensional problem.
The request of tabooing in general is a request for more cognitive work.
Scoring low on a specific test is something more complex than a label. Changing a vague term with a operationalised term is something that often makes sense for tabooing.
I think you confuse cognitive work with explicitely describing cognitive work. When it comes to speaking about negative features of other people it's worthwhile not to say every negative thing that can be said publically.
What do you mean with "failed at learning Python"?
I tried to learn it on my own first, and didn't really pick up on anything.
I tried to learn it at university then, and failed that course.
As more and more helpful resources came online, I tried learning from them, and didn't end up learning it. I think my brain works very differently to most people. There are some things which simply require a kind of functioning I really don't have. It seems languages are the frontier of that - where I have it in me to learn exceptions, whereas I can't learn most. It does seem to generalise to languages - I couldn't even become bilingual even though my parents speak another language and continuously tried to teach it to me, then sent me through school for it. At one point I learned how to read in this one other language and latter forget - can't read that stuff at all now, which is kinda odd.
Anyway, I've managed to learn Stata. And R is for statistical programming like Stata. So, I suspect I could learn it. Though, Stata is more GUI-like and you can't do machine learning with it.
The fact that made Stata easier to learn is that it's GUI like. R isn't. I see no reason to believe that learning R on a level where you can do machine learning with it is easier than learning python. Python has much better documentation than R. It has functions that are much more reasonably named.
I don't really think this is the case, since you are using correctly English, which is far more complicated than Python. Just to be clear: complicated = has more rules and is more ambiguous.
Formal languages require quite a different kind of thinking than natural ones do. It's not just a matter of comparing their complexity.
Unfortunately, there's only one study about the neuropsychology of programming language, but it does contradict your assertion.
Or at least, if it requires a different thinking, that thinking is done with the same area used for natural language.
That's really not how primary v.s secondary language acquisition works. Also k. complexity isn't the same as cognitive complexity.
I know of only one study on the neurobiology of programming language comprehension. It stacks evidence in favor of the theory that the brain uses the same areas of the brain associated with natural language processing (BA 6/44).
On the other hand, studies in bilingual aphasia shows conflicting evidence: some patients lose/recover only one of the language following a brain lesion, while others shows modifications at both languages at the same time.
So, if you think you have neurological deficiencies regarding the acquisition of Python, I think (wild speculation ahead) that you should show other signs of impairment in the acquisition/use of primary/secondary language. For example, were you able to learn Mata?
Regarding K complexity, the difference in cognitive load is exactly my point: if for you manipulating something that has low complexity has higher complexity, it means that something is wrong in the way you learned it.
*Great research. Thanks for looking at the evidence, I didn't know those things and I'll try to take (admittently, a very poor and unbacked up claim on my part that I'm sorry for) your approach in the future.
*I have yet to try learning Mata -I'm unclear of its applications. But, I've shown decent skill in the basic neuropsychological components of second language aquisition from military intelligence analysis testing. On the other hand I've been fairly bad at learning languages at school. May just have been the classroom format though!
Didn't think of it that way. Wow!
Edit: It's just hit me how complex this phrase is:
I can't even conceive of what level of abstraction to place 'the way I learned a given thing' between the sandwhiches of cognitive and k complexity...
In fact that may be because it's incommesurable within the domain of discourse of computational complexity