Direct Installation

Introduction

Below you can find detailed instructions for preparing and configuring environment for PHP directly on your machine.

1. Installing PHP 8.3 (Latest Stable Version as of April 2024)

For Windows:

1. Download the latest PHP 8.3 version from the official PHP website (https://windows.php.net/download/)

2. Extract the ZIP file to a directory (e.g., C:\php)

3. Add the PHP directory to your system's PATH environment variable

4. Rename php.ini-development to php.ini in the PHP directory

For macOS:

brew install php@8.3
echo 'export PATH="/usr/local/opt/php@8.3/bin:$PATH"' >> ~/.zshrc
source ~/.zshrc

For Linux (Ubuntu/Debian):

sudo apt update
sudo apt install software-properties-common
sudo add-apt-repository ppa:ondrej/php
sudo apt update
sudo apt install php8.3 php8.3-cli php8.3-common

2. Configuring PHP for Optimal Performance

Edit your php.ini file:

memory_limit = 512M
max_execution_time = 300
error_reporting = E_ALL
display_errors = On
opcache.enable = 1
opcache.memory_consumption = 128

3. Setting Up a Web Server

Apache (with mod_php):

# For Ubuntu/Debian
sudo apt install apache2 libapache2-mod-php8.3
sudo a2enmod php8.3
sudo systemctl restart apache2

Nginx (with PHP-FPM):

# For Ubuntu/Debian
sudo apt install nginx php8.3-fpm
sudo systemctl start php8.3-fpm
sudo systemctl enable php8.3-fpm

Configure Nginx to work with PHP-FPM (edit /etc/nginx/sites-available/default):

location ~ \.php$ {
    fastcgi_pass unix:/var/run/php/php8.3-fpm.sock;
    fastcgi_index index.php;
    include fastcgi_params;
}

4. Installing Necessary PHP Extensions for Machine Learning

sudo apt install php8.3-xml php8.3-mbstring php8.3-curl php8.3-gd php8.3-zip php8.3-mysql php8.3-bcmath

5. Setting Up Composer (Package Manager)

php -r "copy('https://getcomposer.org/installer', 'composer-setup.php');"
php composer-setup.php
php -r "unlink('composer-setup.php');"
sudo mv composer.phar /usr/local/bin/composer

6. Installing Popular PHP Machine Learning Libraries

composer require php-ai/php-ml
composer require rubix/ml

7. Configuring IDE

1. Install PHPStorm or VS Code

2. Install PHP extensions (for VS Code):

   • PHP IntelliSense

   • PHP Debug

   • PHP Intelephense

8. Setting Up Version Control (Git)

sudo apt install git
git config --global user.name "Your Name"
git config --global user.email "[e-mail]"

9. Configuring a Database System (MySQL)

sudo apt install mysql-server
sudo mysql_secure_installation

Configure PHP to work with MySQL:

sudo apt install php8.3-mysql

10. Setting Up a Virtual Environment

Install and use PHP's built-in development server for isolated projects:

mkdir my_ml_project
cd my_ml_project
php -S localhost:8000

11. Testing the Setup

Create a phpinfo.php file in your web server's document root:

<?php
phpinfo();
?>

Access this file through your web browser to verify your PHP configuration.

12. Creating a Simple ML Test Script

We'll create two test scripts, one for each library, to verify that both PHP-ML and Rubix ML are working correctly.

PHP-ML Test Script

Create a file named php_ml_test.php in your public directory:

<?php
require_once __DIR__ . '/../vendor/autoload.php';

use Phpml\Classification\KNearestNeighbors;

$samples = [[1, 3], [1, 4], [2, 4], [3, 1], [4, 1], [4, 2]];
$labels = ['a', 'a', 'a', 'b', 'b', 'b'];

$classifier = new KNearestNeighbors();
$classifier->train($samples, $labels);

$prediction = $classifier->predict([3, 2]);
echo "Prediction: " . $prediction;

Rubix ML Test Script

Create another file named rubix_ml_test.php in your public directory:

<?php
require_once __DIR__ . '/../vendor/autoload.php';

use Rubix\ML\Classifiers\KNearestNeighbors;
use Rubix\ML\Datasets\Labeled;

$samples = [[1, 3], [1, 4], [2, 4], [3, 1], [4, 1], [4, 2]];
$labels = ['a', 'a', 'a', 'b', 'b', 'b'];

$dataset = new Labeled($samples, $labels);

$estimator = new KNearestNeighbors(3);
$estimator->train($dataset);

$prediction = $estimator->predict([[3, 2]]);
echo "Rubix ML Prediction: " . $prediction[0] . "\n";

To run these scripts, use the following commands:

php php_ml_test.php
php rubix_ml_test.php

If everything is set up correctly, you should see a prediction output.