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Have you read the article? I make it pretty apparent that JS is used primarily for its educational value :)

by bkanber 13y ago

TeeWEE 13y ago
To be honest i didn't initially. I just read it. I think it is a noble thing to explain this in JS. But i don't think "because every body uses js" is a good reason to choose js. However your specific use case makes sense. But in a broader sense I see more and more people fleeing to JS because its what they know.
- thrush 13y ago
  What alternatives would you recommend for someone new to programming and CS? I guess fleeing implies that they were using other tools already, but a lot of new devs are going to JS because it just makes sense to start there (lots of flexibility, hyperactive community, education value).
  - stusmall 13y ago
    If you are at the point of your CS education that you are taking a serious look at machine learning and understanding the theory then you shouldn't have a problem translating into whatever your language of choice is. I get why a teacher would just want to pick a language and say "this is what it is in" but I don't get people who need CS concepts taught in their language of choice. The hard part is the theory and not the implementation. When I took it in university it was taught in language agnostic psuedocode and we were free to use any language from a long list for our assignments.
    - bkanber 13y ago
      > If you are at the point of your CS education that you are taking a serious look at machine learning and understanding the theory then you shouldn't have a problem translating into whatever your language of choice is. This feels like begging the question. Why does that need to be the case? Why can't someone strive to learn machine learning _without_ learning a new language? Why can't they get a head start on the concepts early in their career? Is there some requirement that ML _must_ be an advanced topic, only accessible to polyglots that I haven't heard about?
      - stusmall 13y ago
        Because the nature of the subject requires a fair amount of background. To truly understand the subject and a lot of the approaches a firm understand of statistics, data structures, and even some calculus. Usually by the time someone these subjects down enough for anything substantial in ML then they've seen enough different languages to suss out the general idea of most algorithm sample code. I'm not saying there isn't room for the easier to understand and easier to read guides to ML. More the better, Mitchell was a beast to read through. Its just the language isn't the hard part of the subject. You are the author of the link, correct? I read through some of it, and its approaches the theory and subject matter in a gentle way which is what matters. The sample code is easy to read. I've written maybe 100 lines of js in my life and avoid all web dev like the plague. Your guide is well written and useful. I am not dogging it at all and please don't take it that way. I think its great! What I'm saying is if someone is saying to themselves "I would be able to learn machine learning if only their was a guide in X" then they are probably mistaken. The code is easy, the math and theory is what is hard.
        bkanber 13y ago
        > Its just the language isn't the hard part of the subject. For you, sure -- but not for everyone. This series has actually been up for a little over a year now. I get emails from people who didn't know what machine learning was before they started reading the articles, and now they're building some of the most creative and beautiful projects out there. I also get emails from people who need to implement ML in JS or C-like languages but have had trouble seeing the algorithms in full relief when translating from Python, for instance. The point is, your experience is not everyone's experience. My goal is purely one of accessibility of education. There are smart, talented people who never played with ML simply because they didn't want to dive into a different language, different platform, and different environment just to muck around. There are people who hadn't heard of ML before, but tried it out because JS was right there for them. There are people who stayed away from ML because they thought higher math and a CS education were requirements. Those are facts. This series serves all those people, and it serves them well.
        13y ago

Have you read the article? I make it pretty apparent that JS is used primarily for its educational value :)

by bkanber 13y ago

Have you read the article? I make it pretty apparent that JS is used primarily for its educational value :)

To be honest i didn't initially. I just read it. I think it is a noble thing to explain this in JS. But i don't think "because every body uses js" is a good reason to choose js. However your specific use case makes sense. But in a broader sense I see more and more people fleeing to JS because its what they know.

thrush 13y ago
What alternatives would you recommend for someone new to programming and CS? I guess fleeing implies that they were using other tools already, but a lot of new devs are going to JS because it just makes sense to start there (lots of flexibility, hyperactive community, education value).
- stusmall 13y ago
  If you are at the point of your CS education that you are taking a serious look at machine learning and understanding the theory then you shouldn't have a problem translating into whatever your language of choice is. I get why a teacher would just want to pick a language and say "this is what it is in" but I don't get people who need CS concepts taught in their language of choice. The hard part is the theory and not the implementation. When I took it in university it was taught in language agnostic psuedocode and we were free to use any language from a long list for our assignments.
  - bkanber 13y ago
    > If you are at the point of your CS education that you are taking a serious look at machine learning and understanding the theory then you shouldn't have a problem translating into whatever your language of choice is. This feels like begging the question. Why does that need to be the case? Why can't someone strive to learn machine learning _without_ learning a new language? Why can't they get a head start on the concepts early in their career? Is there some requirement that ML _must_ be an advanced topic, only accessible to polyglots that I haven't heard about?
    - stusmall 13y ago
      Because the nature of the subject requires a fair amount of background. To truly understand the subject and a lot of the approaches a firm understand of statistics, data structures, and even some calculus. Usually by the time someone these subjects down enough for anything substantial in ML then they've seen enough different languages to suss out the general idea of most algorithm sample code. I'm not saying there isn't room for the easier to understand and easier to read guides to ML. More the better, Mitchell was a beast to read through. Its just the language isn't the hard part of the subject. You are the author of the link, correct? I read through some of it, and its approaches the theory and subject matter in a gentle way which is what matters. The sample code is easy to read. I've written maybe 100 lines of js in my life and avoid all web dev like the plague. Your guide is well written and useful. I am not dogging it at all and please don't take it that way. I think its great! What I'm saying is if someone is saying to themselves "I would be able to learn machine learning if only their was a guide in X" then they are probably mistaken. The code is easy, the math and theory is what is hard.
      - bkanber 13y ago
        > Its just the language isn't the hard part of the subject. For you, sure -- but not for everyone. This series has actually been up for a little over a year now. I get emails from people who didn't know what machine learning was before they started reading the articles, and now they're building some of the most creative and beautiful projects out there. I also get emails from people who need to implement ML in JS or C-like languages but have had trouble seeing the algorithms in full relief when translating from Python, for instance. The point is, your experience is not everyone's experience. My goal is purely one of accessibility of education. There are smart, talented people who never played with ML simply because they didn't want to dive into a different language, different platform, and different environment just to muck around. There are people who hadn't heard of ML before, but tried it out because JS was right there for them. There are people who stayed away from ML because they thought higher math and a CS education were requirements. Those are facts. This series serves all those people, and it serves them well.
        13y ago