5 ms·

Generally when I see links to github projects on HN I expect something useful or extraordinary and this looks like my Neural Networks 101 assignment, only far m

Generally when I see links to github projects on HN I expect something useful or extraordinary and this looks like my Neural Networks 101 assignment, only far more polished. But people seem to like it(over 400 stars right now) so maybe I am missing something.

fao_ 9y ago
People like it because it does what it says on the tin without any further dependencies and having to pull in the entire planet, as with the respective node.js binaries.
torstenvl 9y ago
So... if its usefulness is equal to something you've made, AND it's available to the public, AND it's more polished... why exactly are you shitposting about it? Let people enjoy things.
- didymospl 9y ago
  I just pointed out that this is a very basic code. It's definitely not something I would use in any real life scenario(see other posts itt). And if you want to learn about NN you'd be better off googling something like 'backpropagation example' as this project does is virtually not documented. I personally don't find it useful and it takes up the space that can be filled with more interesting content. How is that 'shitposting'?
  - hoffa 9y ago
    It's a refreshingly clean, tiny library without dependencies that can do some cool stuff. Let people like things. Stop shitposting.
    - glouwbug 9y ago
      Thankyou for the kind words.
- nl 9y ago
  It's not shitposting. One of the core requirements of modern deep neural networks is performance. The high accuracy you get from very fast training over large amounts of data is the only reason to look at neural networks over very fast, very accurate systems like XGBoost. If something doesn't deliver that, then it's worth pointing out that it is inadequate for anything but toy tasks.
  - foldr 9y ago
    It's not really worth pointing this out when the thing in question is a 200 line C library. People won't be expecting it to save the world and/or butter their toast.
    - kuroguro 9y ago
      +1 also these tiny libraries are great for learning the basics. All of the code has actual meaning behind it and it's super easy to get it up and running.
      - p1esk 9y ago
        No. You definitely don't want to look at C code when you want to learn NN basics.
- sctb 9y ago
  Please make your point without gratuitous inflammation like “shitposting”. Its effect on the threads should be apparent, and we're trying for better here.
cabaalis 9y ago
Lucky you to have a neural networks 101! My CS degree is now 12 years old, and I crave simple examples like this one. Hence the upvote.
- p1esk 9y ago
  There is a ton of much better tutorials online (e.g. [1]) if you want a NN 101 course. [1] http://neuralnetworksanddeeplearning.com/chap1.html#implementing_our_network_to_classify_digits http://neuralnetworksanddeeplearning.com/chap1.html#implemen...

fao_ 9y ago

People like it because it does what it says on the tin without any further dependencies and having to pull in the entire planet, as with the respective node.js binaries.

torstenvl 9y ago

So... if its usefulness is equal to something you've made, AND it's available to the public, AND it's more polished... why exactly are you shitposting about it? Let people enjoy things.

didymospl 9y ago
I just pointed out that this is a very basic code. It's definitely not something I would use in any real life scenario(see other posts itt). And if you want to learn about NN you'd be better off googling something like 'backpropagation example' as this project does is virtually not documented. I personally don't find it useful and it takes up the space that can be filled with more interesting content. How is that 'shitposting'?
- hoffa 9y ago
  It's a refreshingly clean, tiny library without dependencies that can do some cool stuff. Let people like things. Stop shitposting.
  - glouwbug 9y ago
    Thankyou for the kind words.
nl 9y ago
It's not shitposting. One of the core requirements of modern deep neural networks is performance. The high accuracy you get from very fast training over large amounts of data is the only reason to look at neural networks over very fast, very accurate systems like XGBoost. If something doesn't deliver that, then it's worth pointing out that it is inadequate for anything but toy tasks.
- foldr 9y ago
  It's not really worth pointing this out when the thing in question is a 200 line C library. People won't be expecting it to save the world and/or butter their toast.
  - kuroguro 9y ago
    +1 also these tiny libraries are great for learning the basics. All of the code has actual meaning behind it and it's super easy to get it up and running.
    - p1esk 9y ago
      No. You definitely don't want to look at C code when you want to learn NN basics.
sctb 9y ago
Please make your point without gratuitous inflammation like “shitposting”. Its effect on the threads should be apparent, and we're trying for better here.

cabaalis 9y ago

Lucky you to have a neural networks 101! My CS degree is now 12 years old, and I crave simple examples like this one. Hence the upvote.

p1esk 9y ago
There is a ton of much better tutorials online (e.g. [1]) if you want a NN 101 course. [1] http://neuralnetworksanddeeplearning.com/chap1.html#implementing_our_network_to_classify_digits http://neuralnetworksanddeeplearning.com/chap1.html#implemen...