The fundamental problems of classical machine learning are: Machine learning models require big data to train Machine learning models cannot extrapolate out of the their training data well Machine learning models are not interpretable However, in our recent paper, we have shown that this does not have to be the case. In Universal Differential Equations for Scientific Machine Learning, we start by showing the following figure: Indeed, it shows that by only seeing the tiny first part of the time series, we can automatically learn the equations in such a manner that it predicts the time series will be cyclic in the future, in a way that even gets ... READ MORE

Have you ever wanted to develop your own package for the Julia programming language? Have you ever wanted to contribute a bug fix? Then this tutorial is for ...

Очень часто, при решении задач анализа и подготовки данных, пишут одноразовые скрипты, поддержка и развитие которых не предусматривается вообще. Такой подход им...