Abstract: This tutorial explores the class of non-parametric time series basis decomposition methods particularly suited for nonstationary time series known as Empirical Mode Decomposition (EMD). In ...

Since 2006, we’ve posted over 3,000 videos on YouTube and received over 35 million views, and have no plans of slowing down!

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

The mechanical response of linear viscoelastic materials is often described with Generalized Maxwell models. The necessary material model parameters are typically identified by fitting a Prony series ...

An exercise-driven course on Advanced Python Programming that was battle-tested several hundred times on the corporate-training circuit for more than a decade. Written by David Beazley, author of the ...