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

Learn how to perform a least squares fit using Web-Based VPython! 🐍📊 This tutorial walks you step by step through data fitting, plotting, and analyzing results with VPython in a web environment.

Learn how to solve boundary value problems in Python using the finite difference method! 🐍📐 This tutorial walks you step-by-step through setting up the problem, discretizing the domain, and ...

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 ...

With countless applications and a combination of approachability and power, Python is one of the most popular programming ...

Abstract: A Time-series investigation is a simple technique for dividing information from reconsideration perceptions on a solitary unit or individual at ordinary stretches over countless perceptions.