Dot Physics on MSN

Python physics lesson 18: Learning numerical integration

Dive into Python Physics Lesson 18 and master numerical integration! In this tutorial, we explain step by step how to use Python to approximate integrals, solve physics problems, and analyze motion ...
North Penn Now

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
Dot Physics on MSN

Creating a Python simulation of a tipping stick

Learn how to create a Python simulation of a tipping stick! In this video, we guide you step by step through coding a physics-based simulation that models tipping motion, friction, and torque. Perfect ...

So yeah, I vibe-coded a log colorizer—and I feel good about it

Oh, sure, I can “code.” That is, I can flail my way through a block of (relatively simple) pseudocode and follow the flow. I ...
IEEE

Bayesian Neural Networks via MCMC: A Python-Based Tutorial

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

A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection

Abstract: Time series are the primary data type used to record dynamic system measurements and generated in great volume by both physical sensors and online processes (virtual sensors). Time series ...