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ML4Chem

swMATH ID: 32468
Software Authors: Muammar El Khatib, Wibe A de Jong
Description: ML4Chem: A Machine Learning Package for Chemistry and Materials Science. 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.
Homepage: https://ml4chem.dev
Source Code:  https://github.com/muammar/ml4chem
Dependencies: Python
Keywords: Chemical Physics; arXiv_physics.chem-ph; Materials Science; arXiv_cond-mat.mtrl-sci; arXiv_cs.LG; Machine Learning; arXiv_stat.ML
Related Software: Amp; Matplotlib; Adam; Scikit; DScribe; pymatgen; Dask; SciPy; NumPy; ChemML; DeepChem; TensorFlow; Python
Cited in: 0 Publications

Standard Articles

1 Publication describing the Software Year
ML4Chem: A Machine Learning Package for Chemistry and Materials Science
Muammar El Khatib, Wibe A de Jong
2020