perlmeditation
zubenel0
Hi,
<p>Recently I was thinking about if it is possible to make Perl a more attractive option for data science. I know that some great initiatives exist like [id://1233413] or [id://1213987]. On my part, I will try to write a blog post with a particular machine learning task I have chosen. Nevertheless, as <a href="http://blogs.perl.org/users/ovid/2019/10/data-science-and-perl.html">Ovid wrote</a> falling short in data science field is a significant drawback of Perl. How to fix this?</p>
<p>What I thought about as a way to to proceed could be a grant from Perl foundation. It could work only if it would be possible to find someone interested in a project related to Perl and data science and capable to do it. IMO one of the solutions that could help would be to write a book on How to use Perl in Data Science. Again, this idea is not mine as it was mentioned in <a href="http://blogs.perl.org/users/enkidu/2020/02/pdl-episode-vi-a-new-book.html">perlblogs</a> as a desire to have a new PDL book. Maybe with a help from Perl foundation such a project could encompass even more than PDL and include several other modules suited for data science.</p>
<p>Another interesting idea that I have encountered was to create Perl/XS graphics backend as there is a need to have graphic library which can create 2D/3D chart easily - see the comments on <a href="http://blogs.perl.org/users/stephan_loyd/2019/03/data-analysis-and-visualization-in-perl.html">perlblogs</a>. Unfortunately, I know very little about this but I guess that it might be a very hard task... So these are just a couple of examples but actually the main issue is if it is feasible in general - to have a grant for data science using Perl? What do you think? Do you know someone that could be interested in it? Or do you think that this approach is <b>flawed</b> and have some other suggestions? </p>