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 ...

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

Join us to experiment, break things, and imagine new possibilities. Data Club meetings are meetings, not workshops. An introduction to a bit of software is followed by opportunities to try the ...

Explore how to build a DIY electric motor using simple, readily available materials in this detailed tutorial. Watch step-by-step as we construct the rotor, wind the stator coils, assemble the motor ...

Ask the publishers to restore access to 500,000+ books. An icon used to represent a menu that can be toggled by interacting with this icon. A line drawing of the Internet Archive headquarters building ...

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 ...

A fully functional project based on School Management System which uses Python with Django Web Framework. Following Django project contains all the important features which can be in use for the first ...

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.

Have you ever wanted a hands-on way to demonstrate electromagnetism without complex equipment or expensive kits? This simple electromagnetic train project is a high-impact STEM activity that allows ...