On the SitePoint PHP blog they've posted a tutorial showing you how to use the Prediction.IO server to create a movie recommendation application. Prediction.io is "an open source Machine Learning Server built on top of state-of-the-art open source stack for developers and data scientists create predictive engines for any machine learning task".
In this tutorial, I’m going to walk you through PredictionIO, an open-source machine learning server, which allows you to create applications that could do the following: recommend items (e.g. movies, products, food), predict user behavior, identify item similarity and rank items.
You can pretty much build any machine learning application with ease using PredictionIO. You don’t have to deal with numbers and algorithms and you can just concentrate on building the app itself.
The tutorial, the first part of a series, refreshes some older instructions for getting the Prediction.IO system up and running. He walks you through the creation of an AWS instance for the server a few different ways (Vagrant, Docker, etc). He then talks about the use of the Movie API from MovieDB and the two parts of the application that will be implemented on top of it: a learning phase and a recommendation phase. They show how to use Prediction.io to create the recommendation engine and make the new application on top of it. He helps you install some dependencies to use in the PHP side of the application and briefly explains what they're for.
This wraps up part one of the series. In the second part he starts putting this all to use and creates the PHP functionality to lay on top of the machine learning engine and handle learning and recommendations for users.