materialyzeai/maml
Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
This tool helps materials scientists and researchers apply machine learning to predict material properties and simulate material behavior. You input data about crystal and molecule structures, and it outputs predictions for things like potential energy surfaces or atomic local environments. It's designed for anyone working with materials science data who wants to leverage machine learning without deep programming.
449 stars.
Use this if you are a materials scientist or engineer who needs to convert complex material structures into features for machine learning models and then apply those models to predict material properties or simulate interactions.
Not ideal if you need a general-purpose machine learning library for tasks outside of materials science, or if you prefer to build all your machine learning models and feature generation from scratch.
Stars
449
Forks
94
Language
Jupyter Notebook
License
BSD-3-Clause
Category
Last pushed
Mar 02, 2026
Commits (30d)
0
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