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

Abstract: Data-driven Quality of Experience (QoE) modeling using Machine Learning (ML) is a key enabler for future communication networks as it allows accelerated and unbiased QoE modeling while ...

The use of statistics is ubiquitous in astronomy and astrophysics. Modern advances are made possible by the application of increasingly sophisticated tools, often dubbed "data mining", "machine ...

This repository contains the dataset, as well as additional tools and tutorials, for the University of Pittsburgh English Language Institute Corpus (PELIC). To download a file without using a GitHub ...

Open science is a fundamental pillar to promote scientific progress and collaboration, based on the principles of open data, open source and open access. However, the requirements for publishing and ...

Sandra is a Tech enthusiast with a Journalism and Full-stack web development background. She specializes in web development and Cloud technology. For leisure, Sandra enjoys a good thriller, hugging ...

In this project, I imagine working as a data analyst for a mining company called Metals R' Us. I’ve been given data from their flotation plant, where they separate iron from impurities like dirt, sand ...

This project is for educational purposes only. For this project, I act as a data analyst for a mining company. The company mines Iron, and uses a flotation plant to remove impurities from the Iron ...

Data-centric science has been identified as the 4th paradigm of scientific research. We observe that the novelty introduced by this paradigm is twofold. First, the creation of large, interconnected ...