Machine Learning and PHP: A Practical Guide for Web Developers

Many believe that machine learning is exclusively the domain of Python or R. But what if your main stack is PHP, and you dream of adding intelligent features to your projects? The book "Machine Learning and PHP" shatters this stereotype and proves that PHP is a full-fledged tool for working with data and ML algorithms.

This practical guide will take you from the basics of machine learning to creating production-ready solutions in PHP. You will learn how to use powerful libraries (PHP-ML, Rubix ML), embed pre-trained models, and build your own data processing pipelines.

Who is this book for?

• PHP developers who want to add AI/ML to their web applications;
• Backend engineers working with Laravel, Symfony, or Yii;
• Team Leads who want to evaluate PHP's capabilities in Data Science;
• Anyone looking for an alternative to Python for quickly implementing ML features.

What you will learn and be able to do:

• Install and configure the environment for machine learning in PHP;
• Work with core algorithms: regression, classification, clustering;
• Use neural networks in PHP — from perceptrons to multi-layer architectures;
• Integrate PHP models into real web projects (recommendation systems, content moderation, predictive analytics);
• Process natural language (NLP) and work with text data;
• Export/import models between PHP and Python (ONNX, PMML);
• Optimize the performance of ML code in PHP for high loads.

Special attention is given to practical examples: you will create a spam filtering system, a chatbot with simple NLP logic, a recommendation engine for an online store, and an anomaly detector for logs. Each example is accompanied by full code, explanations, and deployment tips.

The book is written in clear language — reading requires confident knowledge of PHP and a basic understanding of mathematics at the high school level. All complex concepts (gradient descent, loss functions, quality metrics) are explained through analogies from web development.

The author, Alexey Voronov, a practicing PHP architect with 12 years of experience, shares his expertise in implementing ML in highload projects. You will get not dry theory, but proven recipes that can be immediately applied in your work.

Expand the boundaries of PHP's capabilities — machine learning is now available to every web developer!