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 create contour plots in Python using NumPy’s meshgrid and Matplotlib. This step-by-step tutorial shows you how to generate grids, compute functions over them, and visualize data ...

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 ...

So, you want to learn Python? That’s cool. A lot of people are getting into it these days because it’s used for all sorts of things, from building websites to analyzing data. If you’re looking for a ...

It has been proposed by E. Gelenbe in 1989. A Random Neural Network is a compose of Random Neurons and Spikes that circulates through the network. According to this model, each neuron has a positive ...

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.

With countless applications and a combination of approachability and power, Python is one of the most popular programming languages for beginners and experts alike. We’ve compiled a list of 10 online ...