flemishgun

4 ms·

1. 1.▲
   by flemishgun 2y ago

   I was surprised to not find the funding freeze discussed on HN yesterday and I am speechless today at some of the comments I am reading in here. Are readers not aware of the scope and impact of this? I will tell you my story: I am funded
2. 2.▲
   by flemishgun 2y ago

   Is the GNAA alive and well???
3. 3.▲
   by flemishgun 2y ago

   This you-know-better-than-me mindset is why all technology is converging to garbage. I can't speak for OP, but for me, you are half correct: I am indeed ultimately searching for answers, but I want the piles of web pages for an hour,
4. 4.▲
   by flemishgun 2y ago

   Tough to say something as blanket as "it's slower"... there are lots of operations in any linear algebra library. It's not a direct comparison with other C++ linear algebra libraries, but hard to say Armadillo is slow b
5. 5.▲
   by flemishgun 2y ago

   I'm surprised people think this, there is also the widely-used Armadillo linear algebra library. In my opinion it has a much nicer syntax. https://arma.sourceforge.net/
6. 6.▲
   by flemishgun 5y ago

   The library is header-only, so that at least makes the packaging process a little easier.
7. 7.▲
   by flemishgun 5y ago

   This toolkit was originally part of the mlpack machine learning library ( https://github.com/mlpack/mlpack ) before it was split out into a separate, standalone effort.
8. 8.▲
   by flemishgun 5y ago

   Personally I don't like depending on musicbrainz or other online sources; any album that enters my collection I manually (and tediously...) tag via information found on discogs and other sources. I get that this is not... a typical de
9. 9.▲
   by flemishgun 5y ago

   Very cool to see more C++-based machine learning efforts. The language still needs a good dataframe abstraction (maybe XFrame?), but with matrix algebra provided by Armadillo/Eigen and other long-time machine learning libraries like m
10. 10.▲
    by flemishgun 5y ago

    100% agree, and there are a number of efforts in the space. mlpack ( https://www.github.com/mlpack/mlpack/ ), Shogun ( https://www.shogun-toolbox.org/ ), and Shark ( https://www.shark-ml.or