Open source deep learning models that programmers can download and run first try

Re:Open source deep learning models that programmers can dow... by davedx on Saturday June 17, 2017 @08:15AM (#14575557)

OK, I see what you're saying. I think you have the same issue with "real" programming languages too. If you compare some very concise Clojure or Scala code with the equivalent in Java, it can be quite hard to understand if you're not very familiar with the language. But I wouldn't necessarily say it's "incredibly bad practice". A Scala programmer can write concise and elegant code that to another Scala programmer is actually faster to understand because of that conciseness. Whereas the same code written with for loops and class method calls and all the boilerplate in Java would take more studying to filter out the low level constructions.

It's about the level of abstraction. And yeah if you don't understand the notation or syntax at the level of abstraction you're studying, it will be very hard.

(FWIW I find Scala code quite hard to understand sometimes, but I also find the more I know about the language, the more comprehensible it gets).

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Re:Open source deep learning models that programmers can dow... by Houshalter on Saturday June 17, 2017 @01:45PM (#14576856)

It's not necessarily the conciseness that's a problem. Using foreach instead of a full for loop is one thing. What I'm complaining about is code in place of an explanation. E.g. imagine coming across some nasty piece of code like this: https://en.wikipedia.org/wiki/Fast_inverse_square_root#Overv...

It doesn't matter how familiar you are with the language. Without an explanation of what the hell is going on, just looking at the code is useless.

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Re:Open source deep learning models that programmers can dow... by davedx on Sunday June 18, 2017 @12:42PM (#14581482)

Now we're talking about documentation. You are correct, no code is conpletely self documenting. But that Quake code is very low level, the opposite of what I think the grandparent doesn't like (very high level abstract notation)

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