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Likely this part at the beginning that exposed the author's anti-intellectualism/ignorance:

"The majority of literature on machine learning, however, is riddled with complex notation, formulae and superfluous language. It puts walls up around fundamentally simple ideas."

That's what got me, it's such a flat out stupid thing to say. Especially the "puts walls up" phrasing to imply that math beyond what the author understands is a conspiracy. Especially from someone who writes code ... which is full of "complex notation", symbols and "superfluous classes/libraries/error checking/abstractions" by the same absurd reasoning.




Hi, author here. I love reading academic papers and I love Math. But it's an unfortunate fact that academic papers make up the majority of the literature on ML — and that their notation, and writing style exclude a large population who would otherwise find them useful. That's all I'm trying to get at here.


They don't exclude people by using math any more than programmers exclude people by using subclasses or anonymous functions.

I too would love to see more entry level ML resources, but we are talking about academic papers here.

Imagine how stupid it would seem if some outsider came in to HN and started telling programmers to dumb down their code when it's open source because their advanced techniques are too hard for a novice to understand off the bat. Instead of optimizing for efficiency, elegance and readability for their peers - the people they are collaborating with to solve actual problems - they're told to cater to novices always.

The language in your post is textbook anti intellectualism isn't it? And strangely entitled. You would certainly not apply these criteria to code but since it's not your field they must cater to your lack of experience? You know better than they how to communicate ML research to other experts?




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