Explore Python Physics Lesson 19 and learn how the Monte Carlo method can approximate Pi with simple yet powerful simulations. In this lesson, we break down the Monte Carlo technique step by step, ...

Dive into Python Physics Lesson 23 and discover what happens when approximations fail in dipole electric fields. In this lesson, we explore the limitations of common approximation methods in physics ...

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

This repository contains a Python tutorial for using the ECCO Central Production version 4 ocean and sea-ice state estimate. Directories within the repository include the (tutorial documentation) and ...

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 ...

Abstract: Simulation is an excellent tool to study real-life systems with uncertainty. Discrete-event simulation (DES) is a common simulation approach to model time-dependent and complex systems.