ML4Chem: A Machine Learning Package for Chemistry and Materials Science

• Main Authors: Khatib, Muammar El, de Jong, Wibe A
• Format: Journal Article
• Language: English
• Published: 01-03-2020
• Subjects: Computer Science - Learning; Physics - Chemical Physics; Physics - Materials Science; Statistics - Machine Learning
• DOI: 10.48550/arxiv.2003.13388

ML4Chem is an open-source machine learning library for chemistry and
materials science. It provides an extendable platform to develop and deploy
machine learning models and pipelines and is targeted to the non-expert and
expert users. ML4Chem follows user-experience design and offers the needed
tools to go from data preparation to inference. Here we introduce its atomistic
module for the implementation, deployment, and reproducibility of atom-centered
models. This module is composed of six core building blocks: data,
featurization, models, model optimization, inference, and visualization. We
present their functionality and easiness of use with demonstrations utilizing
neural networks and kernel ridge regression algorithms.