In recent years, machine learning has become an essential tool for developing intelligent systems. With the rise of artificial neural networks, programming languages such as Python and R have become the go-to options for machine learning implementation. But is PHP a viable alternative? In this presentation, we will explore the potential of PHP for implementing artificial neural networks by examining its limitations compared to other popular languages. We will also demonstrate the application of machine learning in PHP through a case study where we trained a convolutional neural network model to control a prototype of an autonomous vehicle using Raspberry Pi and Nvidia's "DAVE 2" CNN model architecture.