this post was submitted on 23 Nov 2023
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Machine Learning

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I've been diving a lot deeper into some interesting neural network papers recently and I'm looking to try and implement some of the models detailed in the papers. In general, I know that many papers include the code or I can just google the code to implement the model but I want to push myself to start implementing from scratch more.

Could anyone offer some tips on how they got started or gained the skills to be able to implement a model effectively within a few hours? Any advice would be much appreciated!

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[–] DollyNorman@alien.top 1 points 11 months ago (5 children)

I've found https://paperswithcode.com/ and github search & topics useful tools. In my experience implementing a paper from scratch is a fantastic way to gain a deeper understand of a paper. Don't be discouraged, I can't remember a single paper I've tried to implement that provided all the details necessary to implement.

[–] Avistian@alien.top 1 points 11 months ago (4 children)

Out of curiosity - What do you do, when you are missing some key information?

[–] DollyNorman@alien.top 1 points 11 months ago (3 children)

I think this is why implementing is such a useful learning tool. Papers I tried to implement I probably read cover-to-cover 10 or 20 times, as opposed just skimming abstract, method, results.

When missing key info, after searching the paper a few times:

  • my first step was see if I could find anything on paperswithcode or github.
  • failing that, google searches. see if I could find anything on forums, stack exchange sites, reddit.
  • uni library or academic paper web search engines
  • see if any papers that cite the paper I'm implementing give some clue
  • last resort was to look into papers they cite.

That was all the tricks I had, keen to know any more.

[–] DryArmPits@alien.top 1 points 11 months ago

You can also contact the authors to ask them. Most of us are not monsters and will happily talk about our work. :)

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