Machine Learning and PHP: A Practical Guide

The book "Machine Learning and PHP" is a unique guide for web developers who want to go beyond typical CRUD applications and add elements of artificial intelligence to their projects. Contrary to popular belief, PHP is not just about backend and databases. With modern libraries such as PHP-ML, Rubix ML, and built-in data processing functions, you can implement classification, regression, clustering, and even basic neural networks directly on the server side.

The book is aimed at intermediate PHP developers who are already familiar with OOP, Composer, and the basics of working with databases. You won't need deep knowledge of mathematics or Python — all algorithms are explained at an intuitive level with an emphasis on practical implementation.

What you will learn from the book:

• How to install and configure machine learning libraries for PHP (PHP-ML, Rubix ML).
• Basics of data preprocessing: cleaning, normalization, transformation of categorical features.
• Implementation of popular algorithms: linear regression, logistic regression, decision trees, support vector machines.
• Clustering (K-means) and dimensionality reduction (PCA) for analyzing user data.
• Integration of trained models into web applications: prediction, recommendation systems, scoring.
• Working with text data: spam classification, sentiment analysis, keyword extraction.
• Creating simple neural networks using PHP-ML Neural Network.
• Tips for performance optimization and result caching.

Real-life examples:

• A product recommendation system for an online store.
• A module for detecting fraudulent transactions.
• A chatbot with an intent classifier.
• Predicting customer churn based on action history.

All examples are accompanied by ready-to-use code that can be immediately run in your project. The book is written in a lively, accessible language and contains a minimum of theory — a maximum of practice. After reading it, you will be able to confidently apply machine learning in PHP and expand the functionality of your web applications without switching to other languages.

Perfectly suited for developers working with Laravel, Symfony, or vanilla PHP, as well as for anyone who wants to understand how ML can work in a familiar ecosystem.