The goal of maml is not to duplicate functionality already available in other packages. maml relies on well-established packages such as scikit-learn and tensorflow for implementations of ML algorithms, as well as other materials science packages such as pymatgen and matminer for crystal/molecule manipulation and feature generation.
@misc{maml, author = {Chen, Chi and Zuo, Yunxing and Ye, Weike and Ong, Shyue Ping}, title = {{Maml - materials machine learning package}}, year = {2020}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {https://github.com/materialsvirtuallab/maml}, }
Python, Library, Machine Learning, Deep Learning,
Curator: eowre