Real-time machine learning provides statistical methods to obtain actionable, immediate insights in settings where data becomes available in sequential order. After providing an overview of state of the art real-time machine learning algorithms, we discuss how these algorithms can be leveraged from within a Node.js application. We will see why the powerful API of the core stream module makes Node.js a more attractive platform for such tasks compared to languages traditionally used for scientific computing such as R, Python or Julia. Finally, we will discuss best-practices and common pitfalls that one faces when using these algorithms.
