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

The target audience of this workshop are students, researchers, developers, hobbyists and anyone interested in knowing more about Natural Language Processing and Text Analytics. Some very basic ...

Before analyzing a dataset, the first step is acquiring the data. While platforms like Kaggle and data.gov provide a wealth of datasets, one of the most popular platforms for local government data is ...

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.