A Primer about Machine Learning in Catalysis – A Tutorial with Code

Abstract

Based on a well-edited dataset from literature by Schmack et al.[1] this manuscript provides a tutorial-like introduction to Machine Learning (ML) and Data Science (DS) based on the actual programming code in the Python programming language. The study will not only try to illustrate a ML workflow, but will also show important tasks like hyperparameter tuning and data pre-processing which often cover much of the time of an actual study. Moreover, the study spans from classical ML methods to Deep Learning with Neural Networks.