Empowering PHP Developers: A Guide to Machine Learning Frameworks

Master AI in PHP with our expert guide. Discover top frameworks, algorithms, and essential tips for developers. Elevate your skills and projects with precision.

Machine learning has become a buzzword in the tech world, with social media groups and forums flooded with discussions on ML, AI, Python, Tensor Flow, and NumPy. Interestingly, despite PHP’s long-standing presence in the market for over two decades, there hasn’t been much talk about machine learning with PHP. In this article, we’ll explore some of the available frameworks for building machine learning applications using PHP, starting with a basic understanding of AI.

What is AI?

Artificial Intelligence, a branch of computer science, involves a set of computer programs designed to make computers think smartly. In simple terms, AI enables computers to solve complex problems similarly to how the human brain learns and understands issues. The primary goal of AI is to advance computer systems over time, acquiring knowledge in the same way humans encounter problems and develop reasoning, problem-solving, and self-learning capabilities.

Unlike traditional programming, where explicit conditional rules are defined, machine learning employs datasets to train mathematical algorithms. These algorithms then develop their own rules and conditions based on the provided data. Machine learning combines computer science with mathematics, statistics, and probability theory, allowing computer systems to perform tasks that require human-like intelligence.

PHP Libraries for Machine Learning

While many developers are well-versed in PHP for web application development, the release of PHP 7.2 opened up opportunities for ML and AI-related work. Here are a few PHP libraries tailored for machine learning tasks:


RubixML is a high-level machine learning library offering over 40 supervised and unsupervised algorithms to solve various computer problems. With examples available on GitHub, developers can grasp AI concepts, such as those applied in the housing and real estate industry. However, it’s worth noting that RubixML demands the latest PHP version (7.2 or higher) and sophisticated hardware with at least 1GB of dedicated RAM for optimal performance.


PHP-ML is a library specifically developed for handling machine learning tasks in PHP. It includes ML algorithms and data processing APIs for tasks like data cleanup and feature extraction. While PHP-ML may not boast an extensive range of algorithms, it serves the purpose for simple applications requiring tasks like classification, sentiment analysis, and neural networks. It’s an ideal choice for projects that do not require complex hardware and software setups, catering to basic predictions and data analytics needs.

Brainy PHP:

Brainy PHP is a basic PHP class designed to create neural networks. It caters to web developers who are beginners in AI and want to learn AI concepts without diving into new languages like R or Python. This library offers a straightforward introduction to AI without the overhead of learning complex languages.

Key Takeaways

While some powerful algorithms and libraries may appear enticing, their complex configurations and programming languages can pose challenges. For small teams or developers without extensive machine learning experience, PHP-ML or RubixML offer simpler learning curves and cost-effective solutions compared to more intricate libraries.

It’s crucial to recognize that the efficiency of machine learning applications heavily depends on data extraction and processing. For applications dealing with massive datasets and requiring intensive computations, PHP might not be the ideal choice. However, for smaller applications working with datasets in the megabyte range, PHP can be a suitable solution for solving machine learning problems.