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Minimal dependencies; people are starting to get fed up with having to bootstrap and/or compile the planet just to be able to run some software. The situation h
by Annatar 9y ago
Minimal dependencies; people are starting to get fed up with having to bootstrap and/or compile the planet just to be able to run some software. The situation has gotten completely out of hand, especially if one is not on GNU/Linux.
- AstralStorm 9y agoThis does nor preclude the use of threads or SIMD. Essentially this library is a demo toy that will need a lot to work to make useful in real conditions.
- purerandomness 9y agoThat's exactly the point.
- taneq 9y ago> Essentially this library is a demo toy It's 200 lines of C, what were you expecting?
- didymospl 9y agoGenerally 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 agoPeople 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 agoSo... 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 agoI 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'?
- nl 9y agoIt'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 agoIt'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.
- cabaalis 9y agoLucky 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 agoThere 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...
- AstralStorm 9y agoExpected about 100 lines more for actual performance. ;)
- m_eiman 9y agoWhen I'm looking for libraries to use on my Cortex M0 and M3 embedded devices, I prefer small code size to fast execution (as long as it's fast enough) and don't have SIMD and no use for threads. Sometimes size does matter greatly.
- zimpenfish 9y agoThe included test script demonstrates that it can learn to recognise the semeion digits with reasonable accuracy in under a second. I've tested it on the pendigits data (8 points to describe a digit) and it can learn to recognise those with 93% accuracy in 1.5 seconds. What more do you want from 200 lines of code?