A Primer about Machine Learning in Catalysis – A Tutorial with Code
Stefan Palkovits
Abstract
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.
Topics & Concepts
Python (programming language)Computer scienceWorkflowArtificial intelligenceHyperparameterCode (set theory)Programming languageArtificial neural networkMachine learningDatabaseSet (abstract data type)Machine Learning in Materials ScienceTopic ModelingFerroelectric and Negative Capacitance Devices