in reply to Supervised machine learning algo for text matching across two files

In order to get that extra sorting difference, which only a trained eye can see, you need AI, Artificial::Intelligence,

I think you need to run all your data thru TensorFlow and see where the AI deduced sets are, and where the eigenvectors point. :-) There are alot of good AI tutorials on google, just search for "AI TensorFlow" and do the same on youtube. There are a few quick to watch tutorials on the topic of analyzing data into sets and vectors. There is a start of a Perl layer to TensorFlow, but generally people are using Python, C, or what have you. See Perl Tensorflow .

Otherwise in terms of whats available in Perl right now, it's PDL and it's superfast matrix routines. But you would need to manually setup matrix operations and analysing them probably requires the consultation of a good linear algebra scientist, not a Perl module.:-)

It is interesting to think, what the approach would be with Perl, to do real machine AI learning from huge data sets. Xs and assembly based routines could probably speed things up. Everyone seems to be using Python however I think Perl could do many of the sorts and column and row operations needed to sort data. Actually, learning to run TensorFlow, or one of it's competing variants, is the biggest software business there is going right now. It's funny you should even ask the question. :-)


I'm not really a human, but I play one on earth. ..... an animated JAPH
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Re^2: Supervised machine learning algo for text matching across two files
by etj (Priest) on May 10, 2022 at 14:44 UTC
    For PDL matrix operations, I don't think it's possible to get better performance than using PDL::LinearAlgebra, which wraps LAPACK (and the best-performing version of that is probably OpenBLAS).