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

We connected with Florian Winkler to learn how he created such an elegant and informative map that invites exploration.

Sync databases from and to remote systems via SSH Proxy mode for transfers between isolated environments Automatic credential extraction from PHP frameworks ...

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.