[HTML][HTML] Machine learning approaches for the prediction of materials properties
S Chibani, FX Coudert�- Apl Materials, 2020 - pubs.aip.org
We give here a brief overview of the use of machine learning (ML) in our field, for chemists
and materials scientists with no experience with these techniques. We illustrate the workflow
of ML for computational studies of materials, with a specific interest in the prediction of
materials properties. We present concisely the fundamental ideas of ML, and for each stage
of the workflow, we give examples of the possibilities and questions to be considered in
implementing ML-based modeling.
and materials scientists with no experience with these techniques. We illustrate the workflow
of ML for computational studies of materials, with a specific interest in the prediction of
materials properties. We present concisely the fundamental ideas of ML, and for each stage
of the workflow, we give examples of the possibilities and questions to be considered in
implementing ML-based modeling.