Real-Time Machine Learning with Node.js by Philipp Burckhardt, Carnegie Mellon University

; Date: Sun Aug 26 2018

Tags: Node.JS »»»» Node.js Performance

Real-Time Machine Learning with Node.js by Philipp Burckhardt, Carnegie Mellon University

Real-Time Machine Learning with Node.js - Philipp Burckhardt, Carnegie Mellon University - 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.

About the Author(s)

(davidherron.com) David Herron : David Herron is a writer and software engineer focusing on the wise use of technology. He is especially interested in clean energy technologies like solar power, wind power, and electric cars. David worked for nearly 30 years in Silicon Valley on software ranging from electronic mail systems, to video streaming, to the Java programming language, and has published several books on Node.js programming and electric vehicles.

Books by David Herron

(Sponsored)