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Date: Sun, 4 Dec 2022 22:27:00 -0300
Message-ID: <CADK1yXLLPQbjmohAYhnAN6PK+Psn57UMvWKY+egUYvL57O_JGg@mail.gmail.com>
To: j adams <zardozrocks@gmail.com>
Cc: internals <internals@lists.php.net>
Content-Type: multipart/alternative; boundary="00000000000031013d05ef0a9635"
Subject: Re: [PHP-DEV] PHP support for matrix operations - BLAS, LAPACK.
From: deleugyn@gmail.com (Deleu)

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On Sun, Dec 4, 2022, 8:43 PM j adams <zardozrocks@gmail.com> wrote:

> I apologize if I have the wrong mailing list here. I'm hoping ot ask the
> PHP developer community if there's any appetite for functions to handle
> matrix operations and scientific computing.
>
> I took a course on machine learning which had us code solutions using
> matlab/octave. This year I embarked on trying to translate those functions
> to PHP and have been quite surprised to learn that pure php is quite
> inefficient for matrix multiplication. I've been trying to chase down an
> effective way to perform matrix operations in PHP and posting my questions
> and progress on this forum at PHPBuilder:
>
> https://board.phpbuilder.com/d/10403480-converting-matlab-machine-learning-routines-to-php-need-matrix-operations
>
> Fast matrix operations seem to be absolutely critical for machine learning,
> at least for Support Vector Machines and Neural Networks. I know that there
> is a FANN extension, but it seems to me that it would be beneficial for
> PHP's use in scientific applications if it had support -- either natively
> or via some extension -- for matrix operations and possibly other
> statistical or scientific computations. Python has numpy, for example.
>
> How does everyone feel about BLAS or LAPACK extension for PHP? I'm poorly
> equipped to cook up such a thing, but these libraries already exist and
> could offer great improvements in performance.
>

I remember studying some ML algorithms back in 2015 and I felt PHP was
lacking a lot in terms of matrix operations, specially invert a matrix. It
would have been cool to have some fundamental functionalities baked in.

>

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