Surrogate Modelling: Data-driven Models for Machine Learning and Optimization


This article introduces surrogate modelling, creating data-driven models for machine learning and optimization applications, and gives examples of their applications. Furthermore, it presents how to construct surrogate models, lists common surrogate modelling methods, introduces a Python library consisting of implementation of these methods. The outline of this article is: Why Do We Need Surrogate Models… Read More Surrogate Modelling: Data-driven Models for Machine Learning and Optimization

Machine Learning Techniques


In this article, we list fundamental machine learning techniques with their common applications. Furthermore, it also presents example codes and data sets that present how they can be implemented easily in Python via machine learning libraries. Machine learning methods are generally considered under two groups: Supervised Machine Learning and Unsupervised Machine Learning Algorithms. We can… Read More Machine Learning Techniques