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You test your code. We know you do. How else are you sure that your changes don’t break the program? But after you commit, you discard …

Introduction In this session I will focus on Bayesian inference using the integrated nested Laplace approximation (INLA) method. As …

Learning to code can be quite hard. Apart from the difficulties of learning a new language, following a book can be quite boring. From …

Do you want to know how to make elegant and simple reproducible presentations? In this talk, we are going to explain how to do …

Network analysis offers a perspective of the data that broadens and enriches any investigation. Many times we deal with data in which …

The R language is peculiar in many ways, and its approach to object-oriented (OO) programming is just one of them. Indeed, base R …

JupyterLab can be viewed as the evolution of the Jupyter Notebooks, an open-source web application that allows combining interactive …

In this session we will learn how to model and solve optimization problems of different types (linear, nonlinear, continuous and/or …

Stan is a probabilistic programming language for specifying statistical models. Stan provides full Bayesian inference for …

The aim of this tutorial is to show the use of TensorFlow with KERAS for classification and prediction in Time Series Analysis. The …